Nikola Kasabov

@aut.ac.nz

KEDRI (Knowledge Engineering and Discovery Research Institute)
Auckland University of Technology

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Professor Nikola K Kasabov is a Life Fellow of IEEE, Fellow of the Royal Society of New Zealand, Fellow of the INNS College of Fellows, DVF of the Royal Academy of Engineering UK. He has Doctor Honoris Causa from Obuda University, Budapest. He is the Founding Director of KEDRI and Professor Emeritus at the School of Engineering, Computing and Mathematical Sciences at Auckland University of Technology, New Zealand. He is also Visiting Professor at the Institute for Information and Communication Technologies of the Bulgarian Academy of Sciences and Dalian University, China. Kasabov is Director of and member of the advisory board of . Kasabov is Past President of the Asia Pacific Neural Network Society (APNNS) and the International Neural Network Society (INNS). He has been a chair and a member of several technical committees of IEEE Computational Intelligence Society and Distinguished Lecturer of IEEE (2012-2014). He is Editor of Springer Handbook of B

EDUCATION

SOU Pavlikeni
TU Sofia (MSc, PhD)

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Computer Science

FUTURE PROJECTS

505

Scopus Publications

27313

Scholar Citations

77

Scholar h-index

406

Scholar i10-index

Scopus Publications

Comparative performance analysis of quantum feature maps for quantum kernel-based machine learning
Ravi Kumar Jha, Nikola Kasabov, Saugat Bhattacharyya, Damien Coyle, Girijesh Prasad
Scientific Reports, 2026
Quantum algorithms have become a popular research domain in recent times for discovering quantum-enhanced solutions in machine learning applications. Quantum kernels are one of the directions that establish such quantum-enhanced solutions to some extent. This work presents a detailed analysis of the quantum kernel approach leveraging feature maps and relevant hyperparameters to develop enhanced quantum kernels. The study includes a new high-order feature map and assesses five existing state-of-the-art feature maps for enhanced quantum kernel classifiers. Additionally, the significance of the rotational factor as a hyperparameter is highlighted for improving kernel performance. Also, it is analyzed whether different hyperparameter-tuned feature maps can lead to enhanced decision boundaries, demonstrating kernel expressivity. The analysis is undertaken on classification tasks using four different nonlinear datasets of distinct complexity. Comparative evaluations are also made with traditional machine learning models—Support Vector Machines (Linear and RBF), Naïve Bayes, Linear Discriminant Analysis, Decision Tree, Random Forest, Adaptive Boosting, and MLP. Overall, the study demonstrates that a well-tuned quantum feature map can enhance the generalization ability of quantum kernels, making them more effective for broader quantum-enhanced machine learning applications.
eXCube2: Explainable Brain-Inspired Spiking Neural Network Framework for Emotion Recognition from Audio, Visual and Multimodal Audio–Visual Data
N. K. Kasabov, A. Yang, Z. Wang, I. Abouhassan, A. Kassabova, T. Lappas
Biomimetics, 2026
This paper introduces a biomimetic framework and novel brain-inspired AI (BIAI) models based on spiking neural networks (SNNs) for emotional state recognition from audio (speech), visual (face), and integrated multimodal audio–visual data. The developed framework, named eXCube2, uses a three-dimensional SNN architecture NeuCube that is spatially structured according to a human brain template. The BIAI models developed in eXCube2 are trainable on spatio- and spectro-temporal data using brain-inspired learning rules. Such models are explainable in terms of revealing patterns in data and are adaptable to new data. The eXCube2 models are implemented as software systems and tested on speech and video data of subjects expressing emotional states. The use of a brain template for the SNN structure enables brain-inspired tonotopic and stereo mapping of audio inputs, topographic mapping of visual data, and the combined use of both modalities. This novel approach brings AI-based emotional state recognition closer to human perception, provides a better explainability and adaptability than existing AI systems. It also results in a higher or competitive accuracy, even though this was not the main goal here. This is demonstrated through experiments on benchmark datasets, achieving classification accuracy above 80% on single-modality data and 88.9% when multimodal audio–visual data are used, and a “don’t know” output is introduced. The paper further discusses possible applications of the proposed eXCube2 framework to other audio, visual, and audio–visual data for solving challenging problems, such as recognizing emotional states of people from different origins; brain state diagnosis (e.g., Parkinson’s disease, Alzheimer’s disease, ADHD, dementia); measuring response to treatment over time; evaluating satisfaction responses from online clients; cognitive robotics; human–robot interaction; chatbots; and interactive computer games. The SNN-based implementation of BIAI also enables the use of neuromorphic chips and platforms, leading to reduced power consumption, smaller device size, higher performance accuracy, and improved adaptability and explainability. This research shows a step toward building brain-inspired AI systems.
Novel Neuron-Stability Weighted Dynamic Evolving Spiking Neural Network (NSW-DeSNN) for Classification of fMRI Data
Maryam Doborjeh, Zohreh Doborjeh, Nikola Kasabov
Lecture Notes in Computer Science, 2026
TSPFusion:Text-guided semantic perception for infrared and visible image fusion
Xiangyu Qin, Enlong Wang, Shihua Zhou, Bin Wang, Nikola K. Kasabov
Infrared Physics and Technology, 2026
A hybrid spiking neural network - quantum framework for spatio-temporal data classification: a case study on EEG data
Ravi Kumar Jha, Nikola Kasabov, Saugat Bhattacharyya, Damien Coyle, Girijesh Prasad
EPJ Quantum Technology, 2025
The study introduces a hybrid computational framework that combines neuro-inspired information processing using spiking neural networks (SNNs) and quantum information processing using quantum kernels to develop quantum-enhanced machine learning models for spatio-temporal data, demonstrated through the classification of EEG data as a case study. In the proposed SNN-quantum computation (SNN-QC) framework, SNN with spike time information representation is employed to learn spatio-temporal interactions (EEG recorded from multiple channels over time). Frequency-based (rate-based) information as spike frequency state vectors are extracted from the SNN and classified using a quantum classifier. In the latter part, we use the quantum kernel approach utilising feature maps for classification tasks. The proposed SNN-QC is demonstrated on a benchmark EEG dataset to classify three distinct wrist movement tasks in six binary classification setups as a proof of concept. We introduce a novel high-order nonlinear feature map that demonstrates improved performance over state-of-the-art feature maps and several machine learning methods across most of the tasks studied. Furthermore, the role of hyperparameters for enhanced feature maps is also highlighted. The performance of SNN-QC is evaluated using statistical metrics and cross-validation techniques, demonstrating its efficacy across multiple binary classifiers. Quantum hardware validation is conducted using both a superconducting IBM-QPU and a high-fidelity noisy simulation that replicates a real QPU. Furthermore, the results demonstrate that the SNN-QC outperforms models that use statistical features rather than features extracted from the SNN, as the SNN accounts for the temporal interaction between the spatio-temporal input variables. Finally, we conclude that the SNN-QC offers a potential pathway for developing more accurate neuromorphic-quantum enhanced systems that are both energy-efficient and biologically-inspired, well-suited for dealing with spatio-temporal data.
Genetic signatures predict social-cognitive trajectories in ultra-high-risk psychosis: A 24-month longitudinal study
Zohreh Doborjeh, Alexander Sumich, Oleg N. Medvedev, Khan Buchwald, Maryam Doborjeh, Balkaran Singh, Sugam Budhraja, Alexander Merkin, Max Lam, Jie Yin Yee, Tih-Shih Lee, Wilson Goh, Jimmy Lee, Margaret Williams, Edmund M.-K. Lai, Nikola K. Kasabov
Asian Journal of Psychiatry, 2025
BACKGROUND: Identifying biomarkers that predict social and cognitive outcomes in individuals at ultra-high risk (UHR) for psychosis remains a key challenge in preventive psychiatry. While genetic factors contribute to psychosis vulnerability, specific markers that predict individual trajectories of functional decline or resilience are still unclear. METHODS: In a 24-month longitudinal study involving UHR (n = 45) and healthy control participants (n = 54), we investigated for the first time the predictive causal relationship between key immunological genes (FABP5 family and immunoglobulins) and social-cognitive outcomes. Participants completed comprehensive assessments at baseline and four 6-month intervals. We used regression modelling and dynamic Bayesian network analysis to identify predictive relationships between gene expression and behavioral outcomes over time. RESULTS: FABP5 family genes (FABP5P1, FABP5P11, FABP5P9) significantly predicted verbal memory (β = 0.233, p = 0.002); working memory (β = 0.225, p = 0.004), and social skills (β =-0·190, p < 0.029), respectively, at 24 months in the UHR group. Immunoglobulin-related genes showed distinct effects: FCGR2B predicted object recognition ability (β = 0.233, p = 0.014), while GOT2 inversely predicted planning ability (β = -0.147, p = 0.067). Network analysis revealed UHR-specific temporal dependencies absent in controls, with FCGRT emerging as a central node linking genetic markers to changes in processing speed and perceptual closure. CONCLUSIONS: This study provides the first evidence that FABP5 and immunoglobulin-related genetic markers can predict social-cognitive trajectories in individuals at risk for psychosis. These findings support the use of genetic profiling for early identification and highlight new opportunities for personalized preventive strategies in psychiatry.
SAIN: Search-And-INfer, a Mathematical and Computational Framework for Personalised Multimodal Data Modelling with Applications in Healthcare
Cristian S. Calude, Patrick Gladding, Alec Henderson, Nikola Kasabov
Algorithms, 2025
Personalised modelling has become dominant in personalised medicine and precision health. It creates a computational model for an individual based on large data repositories of existing personalised data, aiming to achieve the best possible personal diagnosis or prognosis and derive an informative explanation for it. Current methods are still working on a single data modality or treating all modalities with the same method. The proposed method, SAIN (Search-And-INfer), offers better results and an informative explanation for classification and prediction tasks on a new multimodal object (sample) using a database of similar multimodal objects. The method is based on different distance measures suitable for each data modality and introduces a new formula to aggregate all modalities into a single vector distance measure to find the closest objects to a new one, and then use them for a probabilistic inference. This paper describes SAIN and applies it to two types of multimodal data, cardiovascular diagnosis and EEG time series, modelled by integrating modalities, such as numbers, categories, images, and time series, and using a software implementation of SAIN.
A multispectral pansharpening method based on CNN-DI network with mixture of experts
Zhongyuan Guo, Jia Lei, Shihua Zhou, Bin Wang, Nikola K. Kasabov
Applied Soft Computing, 2025
Machine learning-guided high-definition transcranial direct current stimulation prevents cybersickness
Alexander Hui Xiang Yang, Cristian Galán-Augé, Nikola Kirilov Kasabov, Yusuf Ozgur Cakmak
Virtual Reality, 2025
Extended reality (XR) environments, such as simulators, augmented reality, and virtual reality are major techniques in contemporary AI and entertainment systems. Cybersickness (CS) is a motion-sickness experienced by many users of XR. CS causes debilitating nausea, disorientation, and oculomotor issues. Treatment and prevention for motion-sickness typically involves drugs with sedative properties that impair task performance. These drugs are non-specific to CS and counter intuitive for enabling activity within XR. Our paper finds that there are specific spatiotemporal patterns of brain activity in certain functional networks related to CS and offers a method for the analysis of these patterns. The method can predict CS ahead of its onset and most importantly it suggests what intervention to apply in order to prevent CS in individuals. We apply a novel approach to CS prevention by using our previously developed spiking neural network (SNN) method, which can predict CS using electroencephalogram (EEG) pre-VR usage, before applying neuromodulation to disrupt CS-related functional networks in the brain. This approach provides an additional layer of screening before intervention with high-definition transcranial direct current stimulation (HD-tDCS). The study recruited healthy CS susceptible participants (9 male, 10 female, n = 19, 18–36 years old) and used a within-subjects design. EEG (32-channel, 10–10-configuration) was monitored at seated-rest and processed through the SNN for CS prediction. Immediately following a positive prediction, either sham, anodal or cathodal HD-tDCS was applied at the Cz area (5-min, 1.5 mA, 30 s-ramp-up/down) with subsequent 10-min VR immersion to record CS events. Main results: Cathodal stimulation yielded a significantly higher number of successful preventions compared to anodal (* p = 0.01) and sham (*** p = 0.00056), achieving a large effect size (> 0.8) with a 47% reduction in CS likelihood. Significance: The treatment was hypothesized to work through disruption of activity at the motor processing and planning regions under Cz. The area appears to be a marker of ongoing CS susceptibility, and also a contributor towards the condition.
NEuroMOrphic Neural-Response Decoding System for Adaptive and Personalized Neuro-Prosthetics’ Control
Georgi Rusev, Svetlozar Yordanov, Simona Nedelcheva, Alexander Banderov, Hugo Lafaye de Micheaux, Fabien Sauter-Starace, Tetiana Aksenova, Petia Koprinkova-Hristova, Nikola Kasabov
Biomimetics, 2025
In our previous work, we developed a neuromorphic decoder of intended movements of tetraplegic patients using ECoG recordings from the brain motor cortex, called Motor Control Decoder (MCD). Even though the training data are labeled based on the desired movement, there is no guarantee that the patient is satisfied by the action of the effectors. Hence, the need for the classification of brain signals as satisfactory/unsatisfactory is obvious. Based on previous work, we upgrade our neuromorphic MCD with a Neural Response Decoder (NRD) that is intended to predict whether ECoG data are satisfactory or not in order to improve MCD accuracy. The main aim is to design an actor–critic structure able to adapt via reinforcement learning the MCD (actor) based on NRD (critic) predictions. For this aim, NRD was trained using not only an ECoG signal but also the MCD prediction or prescribed intended movement of the patient. The achieved accuracy of the trained NRD is satisfactory and contributes to improved MCD performance. However, further work has to be carried out to fully utilize the NRD for MCD performance optimization in an on-line manner. Possibility to include feedback from the patient would allow for further improvement of MCD-NRD accuracy.
Modeling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach
Mojgan Hafezi Fard, Krassie Petrova, Nikola Kirilov Kasabov, Grace Y. Wang
Big Data and Cognitive Computing, 2025
Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data
Ravi Kumar Jha, Nikola Kasabov, Damien Coyle, Saugat Bhattacharyya, Girijesh Prasad
Lecture Notes in Computer Science, 2025
Review of deep learning models with Spiking Neural Networks for modeling and analysis of multimodal neuroimaging data
Ayesha Khan, Vickie Shim, Justin Fernandez, Nikola K. Kasabov, Alan Wang
Frontiers in Neuroscience, 2025
A Spiking Neural Network-Quantum Model for Spatiotemporal Data Analysis: An Experimental Framework
Ravi Kumar Jha, Nikola Kasabov, Saugat Bhattacharyya, Damien Coyle, Girijesh Prasad
Proceedings 2025 IEEE International Conference on Quantum Artificial Intelligence Qai 2025, 2025
Genetic Predictors of Social and Cognitive Outcomes in People with Ultra-High-Risk of Psychosis Using Spiking Neural Networks
Zohreh Doborjeh, Balkaran Singh, Alexander Sumich, Maryam Doborjeh, Wilson Wen Bin Goh, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2025
Izhikevich Neurons in NeuCube for Longitudinal Data Classification
Balkaran Singh, Sugam Budhraja, Maryam Doborjeh, Zohreh Doborjeh, Edmund Lai, Nikola Kasabov
Lecture Notes in Computer Science, 2025
NeuroGeMS: An Open-Source GUI Software for Multimodal Modelling in Biomedical Research and Applications
Sugam Budhraja, Balkaran Singh, Samuel Tan, Maryam Doborjeh, Zohreh Doborjeh, Edmund Lai, Wilson Goh, Nikola Kasabov
Communications in Computer and Information Science, 2025
Accurate breast lesion segmentation by exploiting spatio-temporal information with deep recurrent and convolutional network
Mingjian Chen, Hao Zheng, Changsheng Lu, Enmei Tu, Jie Yang, Nikola Kasabov
Journal of Ambient Intelligence and Humanized Computing, 2023
Integrating Spatial and Temporal Information for Violent Activity Detection from Video Using Deep Spiking Neural Networks
Xiang Wang, Jie Yang, Nikola K. Kasabov
Sensors, 2023
A meta-inspired termite queen algorithm for global optimization and engineering design problems
Peng Chen, Shihua Zhou, Qiang Zhang, Nikola Kasabov
Engineering Applications of Artificial Intelligence, 2022
Construction of Multiple Logic Circuits Based on Allosteric DNAzymes
Xin Liu, Qiang Zhang, Xun Zhang, Yuan Liu, Yao Yao, Nikola Kasabov
Biomolecules, 2022
Artificial intelligence: a systematic review of methods and applications in hospitality and tourism
Zohreh Doborjeh, Nigel Hemmington, Maryam Doborjeh, Nikola Kasabov
International Journal of Contemporary Hospitality Management, 2022
Deep semi-supervised learning via dynamic anchor graph embedding in latent space
Enmei Tu, Zihao Wang, Jie Yang, Nikola Kasabov
Neural Networks, 2022
Denoising of Fluorescence Image on the Surface of Quantum Dot/Nanoporous Silicon Biosensors
Yong Liu, Miao Sun, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
Sensors, 2022
Detail preserving low illumination image and video enhancement algorithm based on dark channel prior
Lingli Guo, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
Sensors, 2022
Universal Adversarial Perturbation Generated by Using Attention Information
Zifei Wang, Xiaolin Huang, Jie Yang, Nikola Kasabov
Studies in Systems Decision and Control, 2022
Multispectral Image Enhancement Based on Weighted Principal Component Analysis and Improved Fractional Differential Mask
Weijie Chen, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Geoscience and Remote Sensing Letters, 2022
Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model
Weijie Chen, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
Remote Sensing, 2022
What has social neuroscience learned from hyperscanning studies of spoken communication? A systematic review
Brent A. Kelsen, Alexander Sumich, Nikola Kasabov, Sophie H.Y. Liang, Grace Y. Wang
Neuroscience and Biobehavioral Reviews, 2022
Spiking neural networks for computational intelligence: an overview
Shirin Dora, Nikola Kasabov
Big Data and Cognitive Computing, 2021
Brain-inspired spiking neural networks for decoding and understanding muscle activity and kinematics from electroencephalography signals during hand movements
Kaushalya Kumarasinghe, Nikola Kasabov, Denise Taylor
Scientific Reports, 2021
High-brightness image enhancement algorithm
Yifei Wei, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
Applied Sciences Switzerland, 2021
Design of MRI structured spiking neural networks and learning algorithms for personalized modelling, analysis, and prediction of EEG signals
Samaneh Alsadat Saeedinia, Mohammad Reza Jahed-Motlagh, Abbas Tafakhori, Nikola Kasabov
Scientific Reports, 2021
Dna matrix operation based on the mechanism of the dnazyme binding to auxiliary strands to cleave the substrate
Shaoxia Xu, Yuan Liu, Shihua Zhou, Qiang Zhang, Nikola K. Kasabov
Biomolecules, 2021
Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia
Maryam Doborjeh, Zohreh Doborjeh, Alexander Merkin, Helena Bahrami, Alexander Sumich, Rita Krishnamurthi, Oleg N. Medvedev, Mark Crook-Rumsey, Catherine Morgan, Ian Kirk, Perminder S. Sachdev, Henry Brodaty, Kristan Kang, Wei Wen, Valery Feigin, Nikola Kasabov
Neural Networks, 2021
Video desnowing and deraining via saliency and dual adaptive spatiotemporal filtering
Yongji Li, Rui Wu, Zhenhong Jia, Jie Yang, Nikola Kasabov
Sensors, 2021
Multispectral image change detection based on single-band slow feature analysis
Youxi He, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
Remote Sensing, 2021
Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition from Various Perspectives
Yawen Lu, Nikola Kasabov, Guoyu Lu
Proceedings of the International Joint Conference on Neural Networks, 2021
Emotion Recognition and Understanding Using EEG Data in A Brain-Inspired Spiking Neural Network Architecture
Wael Alzhrani, Maryam Doborjeh, Zohreh Doborjeh, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2021
Deep learning of explainable eeg patterns as dynamic spatiotemporal clusters and rules in a brain‐inspired spiking neural network
Maryam Doborjeh, Zohreh Doborjeh, Nikola Kasabov, Molood Barati, Grace Y. Wang
Sensors, 2021
A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners
Urtats Etxegarai, Eva Portillo, Jon Irazusta, Lucien Koefoed, Nikola Kasabov
European Journal of Operational Research, 2021
NeuroSense: Short-term emotion recognition and understanding based on spiking neural network modelling of spatio-temporal EEG patterns
Clarence Tan, Marko Šarlija, Nikola Kasabov
Neurocomputing, 2021
Evolving spiking neural network model for pm2.5 hourly concentration prediction based on seasonal differences: A case study on data from beijing and shanghai
Hengyuan Liu, Guibin Lu, Yangjun Wang, Nikola Kasabov
Aerosol and Air Quality Research, 2021
Specular Reflection Image Enhancement Based on a Dark Channel Prior
Ye Xin, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Photonics Journal, 2021
An Effective Algorithm for Specular Reflection Image Enhancement
Zhuang Huang, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2021
Studying Transfer of Learning using a BrainInspired Spiking Neural Network in the Context of Learning a New Programming Language
Mojgan Hafezi Fard, Krassie Petrova, Nikola Kasabov, Grace Y. Wang
2021 IEEE Asia Pacific Conference on Computer Science and Data Engineering Csde 2021, 2021
Single-image snow removal based on an attention mechanism and a generative adversarial network
Aiwen Jia, Zhen-Hong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2021
Prediction of acoustic residual inhibition of tinnitus using a brain-inspired spiking neural network model
Philip J. Sanders, Zohreh G. Doborjeh, Maryam G. Doborjeh, Nikola K. Kasabov, Grant D. Searchfield
Brain Sciences, 2021
Preface
Communications in Computer and Information Science, 2021
Stock market movement prediction using evolving spiking neural networks
Rasmi Ranjan Khansama, Vadlamani Ravi, Akshay Raj Gollahalli, Neelava Sengupta, Nikola K. Kasabov, Imanol Bilbao-Quintana
Handbook of Big Data Analytics Applications in ICT Security and Business Analytics, 2021
Prediction of tinnitus masking benefit within a case series using a spiking neural network model
Mithila Durai, Philip J. Sanders, Zohreh Doborjeh, Maryam Doborjeh, Anne Wendt, et al.
Progress in Brain Research, 2021
Interpretability of spatiotemporal dynamics of the brain processes followed by mindfulness intervention in a brain‐inspired spiking neural network architecture
Zohreh Doborjeh, Maryam Doborjeh, Mark Crook-Rumsey, Tamasin Taylor, Grace Y. Wang, David Moreau, Christian Krägeloh, Wendy Wrapson, Richard J. Siegert, Nikola Kasabov, Grant Searchfield, Alexander Sumich
Sensors Switzerland, 2020
An efficient and high quality medical CT image enhancement algorithm
Zhi Li, Zhenhong Jia, Jie Yang, Nikola Kasabov
International Journal of Imaging Systems and Technology, 2020
Using EEG Data and NeuCube for the Study of Transfer of Learning
Mojgan Hafezi Fard, Krassie Petrova, Maryam Doborjeh, Nikola Kasabov
Proceedings 2020 International Conference on Computational Science and Computational Intelligence Csci 2020, 2020
Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks
Elisa Capecci, Jesus L. Lobo, Ibai Laña, Josafath I. Espinosa-Ramos, Nikola Kasabov
Evolving Systems, 2020
Vehicle-Related Scene Segmentation Using CapsNets
Xiaoxu Liu, Wei Qi Yan, Nikola Kasabov
International Conference Image and Vision Computing New Zealand, 2020
A dynamic DNA color image encryption method based on SHA-512
Shihua Zhou, Pinyan He, Nikola Kasabov
Entropy, 2020
Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture
Clarence Tan, Marko Šarlija, Nikola Kasabov
Neural Processing Letters, 2020
A fast image segmentation algorithm based on saliency map and neutrosophic set theory
Sensen Song, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Photonics Journal, 2020
Pulsewidth Modulation-Based Algorithm for Spike Phase Encoding and Decoding of Time-Dependent Analog Data
Ander Arriandiaga, Eva Portillo, Josafath Israel Espinosa-Ramos, Nikola K. Kasabov
IEEE Transactions on Neural Networks and Learning Systems, 2020
Moving object detection in video sequence images based on an improved visual background extraction algorithm
Junhui Zuo, Zhenhong Jia, Jie Yang, Nikola Kasabov
Multimedia Tools and Applications, 2020
Fusionsense: Emotion classification using feature fusion of multimodal data and deep learning in a brain-inspired spiking neural network
Clarence Tan, Gerardo Ceballos, Nikola Kasabov, Narayan Puthanmadam Subramaniyam
Sensors Switzerland, 2020
Universal Adversarial Perturbation Generated by Attacking Layer-wise Relevance Propagation
Zifei Wang, Xiaolin Huang, Jie Yang, Nikola Kasabov
2020 IEEE 10th International Conference on Intelligent Systems is 2020 Proceedings, 2020
Low Illumination Video Image Enhancement
Zhi Li, Zhenhong Jia, Jie Yang, Nikola Kasabov
IEEE Photonics Journal, 2020
Deep learning neural networks: Methods, systems, and applications
Qinglai Wei, Nikola Kasabov, Marios Polycarpou, Zhigang Zeng
Neurocomputing, 2020
Sleep Stage Classification using NeuCube on SpiNNaker: A Preliminary Study
Sugam Budhraja, Basabdatta Sen Bhattacharya, Simon Durrant, Zohreh Doborjeh, Maryam Doborjeh, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2020
A method to improve the accuracy of SAR image change detection by using an image enhancement method
Zhi Li, Zhenhong Jia, luyang liu, Jie Yang, Nikola Kasabov
ISPRS Journal of Photogrammetry and Remote Sensing, 2020
Remote sensing image enhancement based on the combination of adaptive nonlinear gain and the PLIP model in the NSST domain
Lanhua Zhang, Zhenhong Jia, Lucien Koefoed, Jie Yang, Nikola Kasabov
Multimedia Tools and Applications, 2020
A Variable Selection Method of the Selectivity Ratio Competitive Model Population Analysis for Near Infrared Spectroscopy
Yuxi Wang, Zhenhong Jia, Jie Yang, Nikola Kasabov
Guang Pu Xue Yu Guang Pu Fen Xi Spectroscopy and Spectral Analysis, 2020
New avenue for the geriatric depression scale: Rasch transformation enhances reliability of assessment
Alexander G. Merkin, Oleg N. Medvedev, Perminder S. Sachdev, Lynette Tippett, Rita Krishnamurthi, Susan Mahon, Nikola Kasabov, Priya Parmar, John Crawford, Zohreh G. Doborjeh, Maryam G. Doborjeh, Kristan Kang, Nicole A. Kochan, Helena Bahrami, Henry Brodaty, Valery L. Feigin
Journal of Affective Disorders, 2020
Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks
Balint Petro, Nikola Kasabov, Rita M. Kiss
IEEE Transactions on Neural Networks and Learning Systems, 2020
Application of an Improved Focal Loss in Vehicle Detection
Xuanlin He, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020
eSNN for Spatio-Temporal fMRI Brain Pattern Recognition with a Graphical Object Recognition Case Study
Norhanifah Murli, Nikola Kasabov, Nurul Amirah Paham
Advances in Intelligent Systems and Computing, 2020
Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces
Kaushalya Kumarasinghe, Nikola Kasabov, Denise Taylor
Neural Networks, 2020
Multi-spectral image change detection based on single-band iterative weighting and fuzzy C-means clustering
Liyuan Ma, Jia Zhenhong, Jie Yang, Nikola Kasabov
European Journal of Remote Sensing, 2020
Change Detection in Multitemporal Monitoring Images under Low Illumination
Yong Zhu, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2020
Spiking Neural Networks and online learning: An overview and perspectives
Jesus L. Lobo, Javier Del Ser, Albert Bifet, Nikola Kasabov
Neural Networks, 2020
Video Snow Removal Based on Self-Adaptation Snow Detection and Patch-Based Gaussian Mixture Model
Bin Yang, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2020
A fast sand-dust image enhancement algorithm by blue channel compensation and guided image filtering
Yaqiao Cheng, Zhenhong Jia, Huicheng Lai, Jie Yang, Nikola K. Kasabov
IEEE Access, 2020
A Multi-Information Fusion Correlation Filters Tracker
Junnan Wang, Zhenhong Jia, Huicheng Lai, Jie Yang, Nikola K. Kasabov
IEEE Access, 2020
Blue channel and fusion for sandstorm image enhancement
Yaqiao Cheng, Zhenhong Jia, Huicheng Lai, Jie Yang, Nikola K. Kasabov
IEEE Access, 2020
Object Motion Deblurring in Single Image under Static Background
Tengteng Zhang, Sensen Song, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2020
Application of a brain-inspired spiking neural network architecture to odor data classification
Anup Vanarse, Josafath Israel Espinosa-Ramos, Adam Osseiran, Alexander Rassau, Nikola Kasabov
Sensors Switzerland, 2020
Contrast enhancement of medical images using fuzzy set theory and nonsubsampled shearlet transform
Guo Qingrong, Jia Zhenhong, Yang Jie, Nikola Kasabov
International Journal of Imaging Systems and Technology, 2019
Speckle Noise Removal in Image-based Detection of Refractive Index Changes in Porous Silicon Microarrays
Ruyong Ren, Zhiqing Guo, Zhenhong Jia, Jie Yang, Nikola K. Kasabov, Chuanxi Li
Scientific Reports, 2019
Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain
Zohreh Doborjeh, Maryam Doborjeh, Tamasin Taylor, Nikola Kasabov, Grace Y. Wang, Richard Siegert, Alex Sumich
Scientific Reports, 2019
Spiking neural networks for deep learning and knowledge representation: Editorial
Nikola K. Kasabov
Neural Networks, 2019
Personalised modelling with spiking neural networks integrating temporal and static information
Maryam Doborjeh, Nikola Kasabov, Zohreh Doborjeh, Reza Enayatollahi, Enmei Tu, Amir H. Gandomi
Neural Networks, 2019
Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area
Piotr S. Maciąg, Nikola Kasabov, Marzena Kryszkiewicz, Robert Bembenik
Environmental Modelling and Software, 2019
ESPANNet: Evolving Spike Pattern Association Neural Network for Spike-based Supervised Incremental Learning and Its Application for Single-trial Brain Computer Interfaces
Kaushalya Kumarasinghe, Denise Taylor, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2019
Applying speckle noise suppression to refractive indices change detection in porous silicon microarrays
Ruyong Ren, Zhenhong Jia, Jie Yang, Nikola Kasabov
Sensors Switzerland, 2019
Erratum: Change detection in SAR images based on the ROF model semi-implicit denoising method (Sensors, (2019), 19, 1179, 10.3390/s19051179)
Xuemei Lou, Zhenhong Jia, Jie Yang, Nikola Kasabov
Sensors Switzerland, 2019
Change detection of optical remote sensing image disturbed by thin cloud using wavelet coefficient substitution algorithm
Xiaoqian Yang, Zhenhong Jia, Jie Yang, Nikola Kasabov
Sensors Switzerland, 2019
Adaptive long-term traffic state estimation with evolving spiking neural networks
Ibai Laña, Jesus L. Lobo, Elisa Capecci, Javier Del Ser, Nikola Kasabov
Transportation Research Part C Emerging Technologies, 2019
A Computational Model of Neuroreceptor-Dependent Plasticity (NRDP) Based on Spiking Neural Networks
Josafath I. Espinosa-Ramos, Elisa Capecci, Nikola Kasabov
IEEE Transactions on Cognitive and Developmental Systems, 2019
Change detection in SAR images based on the ROF model semi-implicit denoising method
Xuemei Lou, Zhenhong Jia, Jie Yang, Nikola Kasabov
Sensors Switzerland, 2019
Moving Target Detection Based on Improved Gaussian Mixture Background Subtraction in Video Images
Junhui Zuo, Zhenhong Jia, Jie Yang, Nikola Kasabov
IEEE Access, 2019
SAR Image Change Detection Based on Mathematical Morphology and the K-Means Clustering Algorithm
Luyang Liu, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2019
Quasi-noise-free and detail-preserved digital holographic reconstruction
Ruyong Ren, Zhenhong Jia, Jie Yang, Nikola K. Kasabov, Xiaohui Huang
IEEE Access, 2019
Multi-Spectral Image Change Detection Based on Band Selection and Single-Band Iterative Weighting
Liyuan Ma, Zhenhong Jia, Yinfeng Yu, Jie Yang, Nikola K. Kasabov
IEEE Access, 2019
Deep Learning of EEG data in the neucube brain-inspired spiking neural network architecture for a better understanding of depression
Dhvani Shah, Grace Y. Wang, Maryam Doborjeh, Zohreh Doborjeh, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2019
Classification and regression of spatio-temporal signals using NeuCube and its realization on SpiNNaker neuromorphic hardware
Jan Behrenbeck, Zied Tayeb, Cyrine Bhiri, Christoph Richter, Oliver Rhodes, Nikola Kasabov, Josafath I Espinosa-Ramos, Steve Furber, Gordon Cheng, Jörg Conradt
Journal of Neural Engineering, 2019
Modelling Peri-Perceptual Brain Processes in a Deep Learning Spiking Neural Network Architecture
Zohreh Gholami Doborjeh, Nikola Kasabov, Maryam Gholami Doborjeh, Alexander Sumich
Scientific Reports, 2018
Evolving Spiking Neural Networks for online learning over drifting data streams
Jesus L. Lobo, Ibai Laña, Javier Del Ser, Miren Nekane Bilbao, Nikola Kasabov
Neural Networks, 2018
Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters
Cheng Peng, Fanghui Liu, Jie Yang, Nikola Kasabov
IEEE Signal Processing Letters, 2018
Integrating Space, Time, and Orientation in Spiking Neural Networks: A Case Study on Multimodal Brain Data Modeling
Neelava Sengupta, Carolyn B. McNabb, Nikola Kasabov, Bruce R. Russell
IEEE Transactions on Neural Networks and Learning Systems, 2018
Analysis of Gene Expression Time Series Data of Ebola Vaccine response using the NeuCube and Temporal Feature Selection
Lucien Koefoed, Elisa Capecci, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2018
EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes
Zohreh G Doborjeh, Maryam Doborjeh, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2018
FaNeuRobot: A Framework for Robot and Prosthetics Control Using the NeuCube Spiking Neural Network Architecture and Finite Automata Theory
Kaushalya Kumarasinghe, Mahonri Owen, Denise Taylor, Nikola Kasabov, Chi Kit
Proceedings IEEE International Conference on Robotics and Automation, 2018
Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data
Maryam Gholami Doborjeh, Nikola Kasabov, Zohreh Gholami Doborjeh
Evolving Systems, 2018
Densely Connected Discriminative Correlation Filters for Visual Tracking
Cheng Peng, Fanghui Liu, Jie Yang, Nikola Kasabov
IEEE Signal Processing Letters, 2018
A retinotopic spiking neural network system for accurate recognition of moving objects using neucube and dynamic vision sensors
Lukas Paulun, Anne Wendt, Nikola Kasabov
Frontiers in Computational Neuroscience, 2018
An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks
Fahad Bashir Alvi, Russel Pears, Nikola Kasabov
Evolving Systems, 2018
Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework
Obada Al Zoubi, Mariette Awad, Nikola K. Kasabov
Artificial Intelligence in Medicine, 2018
Attentional Bias Pattern Recognition in Spiking Neural Networks from Spatio-Temporal EEG Data
Zohreh Gholami Doborjeh, Maryam G. Doborjeh, Nikola Kasabov
Cognitive Computation, 2018
Evolving and spiking connectionist systems for brain-inspired artificial intelligence
Nikola Kasabov
Artificial Intelligence in the Age of Neural Networks and Brain Computing, 2018
Spiking neural networks for cancer gene expression time series modelling and analysis
Jack Dray, Elisa Capecci, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Unsupervised change detection of SAR images based on an improved NSST algorithm
Pengyun Chen, Zhenhong Jia, Jie Yang, Nikola Kasabov
Journal of the Indian Society of Remote Sensing, 2018
Discrete sparse hashing for cross-modal similarity search
Lu Wang, Chao Ma, Enmei Tu, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Road traffic forecasting using neucube and dynamic evolving spiking neural networks
Ibai Laña, Elisa Capecci, Javier Del Ser, Jesus L. Lobo, Nikola Kasabov
Studies in Computational Intelligence, 2018
Drift detection over non-stationary data streams using evolving spiking neural networks
Jesus L. Lobo, Javier Del Ser, Ibai Laña, Miren Nekane Bilbao, Nikola Kasabov
Studies in Computational Intelligence, 2018
SAR image change detection based on equal weight image fusion and adaptive threshold in the NSST domain
Zhou Wenyan, Jia Zhenhong, Yinfeng Yu, Jie Yang, Nilola Kasabov
European Journal of Remote Sensing, 2018
Analysis, classification and marker discovery of gene expression data with evolving spiking neural networks
Gautam Kishore Shahi, Imanol Bilbao, Elisa Capecci, Durgesh Nandini, Maria Choukri, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
A Spatio-Temporal Fully Convolutional Network for Breast Lesion Segmentation in DCE-MRI
Mingjian Chen, Hao Zheng, Changsheng Lu, Enmei Tu, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
Modelling and analysis of temporal gene expression data using spiking neural networks
Durgesh Nandini, Elisa Capecci, Lucien Koefoed, Ibai Laña, Gautam Kishore Shahi, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2018
New algorithms for encoding, learning and classification of fMRI data in a spiking neural network architecture: A case on modeling and understanding of dynamic cognitive processes
Nikola Kasabov, Lei Zhou, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Jie Yang
IEEE Transactions on Cognitive and Developmental Systems, 2017
A Practical GrabCut Color Image Segmentation Based on Bayes Classification and Simple Linear Iterative Clustering
Dayong Ren, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
IEEE Access, 2017
Speckle Reduction of Reconstructions of Digital Holograms Using Gamma-Correction and Filtering
Xiaohui Huang, Zhenhong Jia, Junlin Zhou, Jie Yang, Nikola Kasabov
IEEE Access, 2017
Spike-time encoding as a data compression technique for pattern recognition of temporal data
Neelava Sengupta, Nikola Kasabov
Information Sciences, 2017
A spiking neural network model for obstacle avoidance in simulated prosthetic vision
Chenjie Ge, Nikola Kasabov, Zhi Liu, Jie Yang
Information Sciences, 2017
Image processing of porous silicon microarray in refractive index change detection
Zhiqing Guo, Zhenhong Jia, Jie Yang, Nikola Kasabov, Chuanxi Li
Sensors Switzerland, 2017
Remote sensing image change detection based on NSCT-HMT model and its application
Pengyun Chen, Yichen Zhang, Zhenhong Jia, Jie Yang, Nikola Kasabov
Sensors Switzerland, 2017
Mapping Temporal Variables Into the NeuCube for Improved Pattern Recognition, Predictive Modeling, and Understanding of Stream Data
Enmei Tu, Nikola Kasabov, Jie Yang
IEEE Transactions on Neural Networks and Learning Systems, 2017
Medical image enhancement method based on improved Gamma correction in Shearlet domain
Guangdianzi Jiguang Journal of Optoelectronics Laser, 2017
Mapping, learning, visualization, classification, and understanding of fMRI Data in the NeuCube evolving spatiotemporal data machine of spiking neural networks
Nikola K. Kasabov, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh
IEEE Transactions on Neural Networks and Learning Systems, 2017
Change detection in SAR images based on the logarithmic transformation and total variation denoising method
Xueguo Wang, Zhenhong Jia, Jie Yang, Nikola Kasabov
Remote Sensing Letters, 2017
A remote sensing image enhancement method using mean filter and unsharp masking in non-subsampled contourlet transform domain
Lu Liu, Zhenhong Jia, Jie Yang, Nikola Kasabov
Transactions of the Institute of Measurement and Control, 2017
Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement
Fei Zhou, ZhenHong Jia, Jie Yang, Nikola Kasabov
Biomed Research International, 2017
Robust kernel approximation for classification
Fanghui Liu, Xiaolin Huang, Cheng Peng, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
Correlation Filters with Adaptive Memories and Fusion for Visual Tracking
Cheng Peng, Fanghui Liu, Haiyan Yang, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
EEG Comparison Between Normal and Developmental Disorder in Perception and Imitation of Facial Expressions with the NeuCube
Yuma Omori, Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola Kasabov, Maryam Gholami Doborjeh
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2017
Adaptive cow movement detection using evolving spiking neural network models
Tao Gao, Nikola Kasabov
Evolving Systems, 2016
Noisy Remote Sensing Image Segmentation with Wavelet Shrinkage and Graph Cuts
Liangliang Li, Zhenhong Jia, Jie Yang, Nikola Kasabov
Journal of the Indian Society of Remote Sensing, 2016
An improved collaborative representation based classification with regularized least square (CRC–RLS) method for robust face recognition
Yu Cheng, Zhigang Jin, Tao Gao, Hongcai Chen, Nikola Kasabov
Neurocomputing, 2016
From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine
Nikola Kasabov, Neelava Sengupta, Nathan Scott
2016 IEEE 8th International Conference on Intelligent Systems is 2016 Proceedings, 2016
Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data
Hao Wu, Lin Gao, Nikola K. Kasabov
IEEE ACM Transactions on Computational Biology and Bioinformatics, 2016
Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series
Pritam Bose, Nikola K. Kasabov, Lorenzo Bruzzone, Reggio N. Hartono
IEEE Transactions on Geoscience and Remote Sensing, 2016
A graph-based semi-supervised k nearest-neighbor method for nonlinear manifold distributed data classification
Enmei Tu, Yaqian Zhang, Lin Zhu, Jie Yang, Nikola Kasabov
Information Sciences, 2016
Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system
Maryam Gholami Doborjeh, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2016
Which method to use for optimal structure and function representation of large spiking neural networks: A case study on the NeuCube architecture
Anne Abbott, Neelava Sengupta, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2016
Longitudinal study of Alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model
Elisa Capecci, Zohreh Gholami Doborjeh, Nadia Mammone, Fabio La Foresta, Francesco C. Morabito, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2016
Remote sensing image enhancement based on the combination of nonsubsampled shearlet transform and guided filtering
Duliang Lv, Zhenhong Jia, Jie Yang, Nikola Kasabov
Optical Engineering, 2016
A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data from Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects
Maryam Gholami Doborjeh, Grace Y. Wang, Nikola K. Kasabov, Robert Kydd, Bruce Russell
IEEE Transactions on Biomedical Engineering, 2016
Cyber fraud detection using evolving spiking neural network
Amit Soni Arya, Vadlamani Ravi, Vadali Tejasviram, Neelava Sengupta, N. Kasabov
11th International Conference on Industrial and Information Systems Iciis 2016 Conference Proceedings, 2016
SAR Image Change Detection Method Based on Pulse-Coupled Neural Network
Rui Liu, Zhenhong Jia, Xizhong Qin, Jie Yang, Nikola Kasabov
Journal of the Indian Society of Remote Sensing, 2016
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications
Nikola Kasabov, Nathan Matthew Scott, Enmei Tu, Stefan Marks, Neelava Sengupta, Elisa Capecci, Muhaini Othman, Maryam Gholami Doborjeh, Norhanifah Murli, Reggio Hartono, Josafath Israel Espinosa-Ramos, Lei Zhou, Fahad Bashir Alvi, Grace Wang, Denise Taylor, Valery Feigin, Sergei Gulyaev, Mahmoud Mahmoud, Zeng-Guang Hou, Jie Yang
Neural Networks, 2016
Evolving Connectionist Systems for Adaptive Learning and Pattern Recognition: From Neuro-Fuzzy-, to Spiking-and Neurogenetic
Nikola Kasabov
Handbook on Computational Intelligence in 2 Volumes, 2016
Hybrid Evolutionary-, Constructive- and Evolving Fuzzy Neural Networks
Michael J. Watts, Nikola Kasabov
Handbook on Computational Intelligence in 2 Volumes, 2016
Efficient recognition of attentional bias using EEG data and the neucube evolving spatio-temporal data machine
Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2016
A spiking neural network for personalised modelling of electrogastrography (EGG)
Vivienne Breen, Nikola Kasabov, Peng Du, Stefan Calder
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2016
Analysis of similarity and differences in brain activities between perception and production of facial expressions using EEG data and the neucube spiking neural network architecture
Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola Kasabov, Maryam Gholami Doborjeh
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2016
A method used for Dotted Data Matrix image processing
Tao Gao, Nikola Kasabov
Journal of Computational Methods in Sciences and Engineering, 2015
Unsupervised detection of different SAR images based on improved NSCT domain image fusion algorithm
Guangdianzi Jiguang Journal of Optoelectronics Laser, 2015
A novel multi-focus image fusion method using PCNN in nonsubsampled contourlet transform domain
Jingjing Wang, Qian Li, Zhenhong Jia, Nikola Kasabov, Jie Yang
Optik, 2015
Feasibility of NeuCube spiking neural network architecture for EMG pattern recognition
Long Peng, Zeng-Guang Hou, Nikola Kasabov, Gui-Bin Bian, Luige Vladareanu, Hongnian Yu
International Conference on Advanced Mechatronic Systems Icamechs, 2015
SEMG-based torque estimation for robot-assisted lower limb rehabilitation
Long Peng, Zeng-Guang Hou, Nikola Kasabov, Jin Hu, Liang Peng, Wei-Qun Wang
Proceedings of the International Joint Conference on Neural Networks, 2015
Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture
Elisa Capecci, Josafath I. Espinosa-Ramos, Nadia Mammone, Nikola Kasabov, Jonas Duun-Henriksen, Troels Wesenberg Kjaer, Maurizio Campolo, Fabio La Foresta, Francesco C. Morabito
Proceedings of the International Joint Conference on Neural Networks, 2015
A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking
Lu Liu, Zhenhong Jia, Jie Yang, Nikola Kasabov, Fellow IEEE
International Journal of Imaging Systems and Technology, 2015
Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment
Elisa Capecci, Nikola Kasabov, Grace Y. Wang
Neural Networks, 2015
Implementation of active training for an upper-limb rehabilitation robot based on impedance control
Liang Peng, Zeng-Guang Hou, Nikola Kasabov, Long Peng, Jin Hu, Weiqun Wang
Proceedings of the 2015 27th Chinese Control and Decision Conference Ccdc 2015, 2015
New Strategy to Reduce the Global Burden of Stroke
Valery L. Feigin, Rita Krishnamurthi, Rohit Bhattacharjee, Priya Parmar, Alice Theadom, Tasleem Hussein, Mitali Purohit, Patria Hume, Max Abbott, Elaine Rush, Nikola Kasabov, Ineke Crezee, Stanley Frielick, Suzanne Barker-Collo, P. Alan Barber, Bruce Arroll, Richie Poulton, Yogini Ratnasabathy, Martin Tobias, Norberto Cabral, Sheila C.O. Martins, Luis E.T.A. Furtado, Patrice Lindsay, Gustavo Saposnik, Maurice Giroud, Yannick Béjot, Werner Hacke, Man Mohan Mehndiratta, Jeyaraj Durai Pandian, Sanjeev Gupta, Vasantha Padma, Dipes Kumar Mandal, Yoshihiro Kokubo, Norlinah Mohamed Ibrahim, Ramesh Sahathevan, Hua Fu, Wenzhi Wang, Liping Liu, Zeng-Guang Hou, António Freire Goncalves, Manuel Correia, Yury Varakin, Michael Kravchenko, Michael Piradov, Mohammed Saadah, Amanda G. Thrift, Dominique Cadilhac, Stephen Davis, Geoffrey Donnan, Alan D. Lopez, Graeme J. Hankey, Annick Maujean, Elizabeth Kendall, Michael Brainin, Foad Abd-Allah, Natan M. Bornstein, Valeria Caso, Juan Manuel Marquez-Romero, Rufus O. Akinyemi, Nasser F. Bin Dhim, Bo Norrving, Shireen Sindi, Miia Kivipelto, Shanthi Mendis, M. Arfan Ikram, Albert Hofman, Saira Saeed Mirza, Peter M. Rothwell, Peter Sandercock, Raad Shakir, Ralph L. Sacco, Antonio Culebras, Gregory A. Roth, Maziar Moradi-Lakeh, Christopher Murray, K.M. Venkat Narayan, George A. Mensah, David Wiebers, Andrew E. Moran
Stroke, 2015
Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance
Enmei Tu, Jie Yang, Nicola Kasabov, Yaqian Zhang
Neurocomputing, 2015
A holistic comparative analysis of diagnostic tests for urothelial carcinoma: A study of Cxbladder Detect, UroVysion® FISH, NMP22® and cytology based on imputation of multiple datasets Data analysis, statistics and modelling
Vivienne Breen, Nikola Kasabov, Ashish M. Kamat, Elsie Jacobson, James M. Suttie, Paul J. O’Sullivan, Laimonis Kavalieris, David G. Darling
BMC Medical Research Methodology, 2015
Evolving connectionist systems for adaptive learning and knowledge discovery: Trends and directions
Nikola K. Kasabov
Knowledge Based Systems, 2015
Identifying overlapping mutated driver pathways by constructing gene networks in cancer
Hao Wu, Lin Gao, Feng Li, Fei Song, Xiaofei Yang, Nikola Kasabov
BMC Bioinformatics, 2015
Evolving personalized modeling system for integrated feature, neighborhood and parameter optimization utilizing gravitational search algorithm
Wen Liang, Yingjie Hu, Nikola Kasabov
Evolving Systems, 2015
Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast
Jing-jing Wang, Zhen‐hong Jia, Nikola Kasabov
International Journal of Imaging Systems and Technology, 2015
Integrative Computational Neurogenetic Modeling
N.K. Kasabov
Brain Mapping an Encyclopedic Reference, 2015
Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes
Nikola Kasabov, Elisa Capecci
Information Sciences, 2015
Neuromorphic predictive systems based on deep learning
Communications in Computer and Information Science, 2015
Evolving connectionist systems: From neuro-fuzzy-, to spiking- and neuro-genetic
Nikola Kasabov
Springer Handbook of Computational Intelligence, 2015
Dynamic 3D clustering of spatio-temporal brain data in the neucube spiking neural network architecture on a case study of fMRI data
Maryam Gholami Doborjeh, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015
Inference of cancer progression from somatic mutation data
Hao Wu, Lin Gao, Nikola Kasabov
IFAC Papersonline, 2015
Framework for knowledge driven optimisation based data encoding for brain data modelling using spiking neural network architecture
Neelava Sengupta, Nathan Scott, Nikola Kasabov
Advances in Intelligent Systems and Computing, 2015
Artificial Neural Networks - Methods and Applications in Bio-/Neuroinformatics: Preface
Artificial Neural Networks Methods and Applications in Bio Neuroinformatics, 2015
Abnormal activity detection using spatio-temporal feature and Laplacian sparse representation
Yu Zhao, Yu Qiao, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015
Poisson image denoising based on BLS-GSM method
Liangdong Li, Nikola Kasabov, Jie Yang, Lixiu Yao, Zhenghong Jia
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015
A feasibility study of using the neucube spiking neural network architecture for modelling Alzheimer’s disease EEG data
Elisa Capecci, Francesco Carlo Morabito, Maurizio Campolo, Nadia Mammone, Domenico Labate, Nikola Kasabov
Smart Innovation Systems and Technologies, 2015
Adaptive location for multiple salient objects detection
Shaoyong Jia, Yuding Liang, Xianyang Chen, Yun Gu, Jie Yang, Nikola Kasabov, Yu Qiao
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2015
An enhanced multiphase Chan-Vese model for the remote sensing image segmentation
Xin Yi, Yingjie Hu, Zhenhong Jia, Liejun Wang, Jie Yang, Nikola Kasabov
Concurrency and Computation Practice and Experience, 2014
Remote sensing image change detection based on minimum spanning tree clustering
Guangdianzi Jiguang Journal of Optoelectronics Laser, 2014
A novel graph-based k-means for nonlinear manifold clustering and representative selection
Enmei Tu, Longbing Cao, Jie Yang, Nicola Kasabov
Neurocomputing, 2014
EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation
Jin Hu, Zeng-Guang Hou, Yi-Xiong Chen, Nikola Kasabov, Nathan Scott
Proceedings of the IEEE Ras and EMBS International Conference on Biomedical Robotics and Biomechatronics, 2014
Extracting temporal knowledge from time series: A case study in ecological data
Reggio N Hartono, Russel Pears, Nikola Kasabov, Susan P Worner
Proceedings of the International Joint Conference on Neural Networks, 2014
NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data
Enmei Tu, Nikola Kasabov, Muhaini Othman, Yuxiao Li, Susan Worner, Jie Yang, Zhenghong Jia
Proceedings of the International Joint Conference on Neural Networks, 2014
Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data
Muhaini Othman, Nikola Kasabov, Enmei Tu, Valery Feigin, Rita Krishnamurthi, Zhengguang Hou, Yixiong Chen, Jin Hu
Proceedings of the International Joint Conference on Neural Networks, 2014
Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications
Denise Taylor, Nathan Scott, Nikola Kasabov, Elisa Capecci, Enmei Tu, Nicola Saywell, Yixong Chen, Jin Hu, Zeng-Guang Hou
Proceedings of the International Joint Conference on Neural Networks, 2014
Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke
Nikola Kasabov, Valery Feigin, Zeng-Guang Hou, Yixiong Chen, Linda Liang, Rita Krishnamurthi, Muhaini Othman, Priya Parmar
Neurocomputing, 2014
Foreword
Shafiq Alam, Gillian Dobbie, Yun Sing Koh, Saeed ur Rehman
Biologically Inspired Techniques for Knowledge Discovery and Data Mining, 2014
Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model
Maryam Gholami Doborjeh, Elisa Capecci, Nikola Kasabov
IEEE Ssci 2014 2014 IEEE Symposium Series on Computational Intelligence Eals 2014 2014 IEEE Symposium on Evolving and Autonomous Learning Systems Proceedings, 2014
Springer handbook of bio-/neuroinformatics
Nikola Kasabov, Krishnamurthi, R, Kasabov, N, Feigin, V
Springer Handbook of Bio Neuroinformatics, 2014
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
Nikola K. Kasabov
Neural Networks, 2014
Brain-like information processing for spatio-temporal pattern recognition
Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Brain, gene, and quantum inspired computational intelligence
Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Understanding nature through the symbiosis of information science, bioinformatics, and neuroinformatics
Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Preface
Nikola Kasabov, Krishnamurthi, R, Kasabov, N, Feigin, V
Springer Handbook of Bio Neuroinformatics, 2014
Computational neurogenetic modeling: Gene-dependent dynamics of cortex and idiopathic epilepsy
Lubica Benuskova, Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Computational modeling with spiking neural networks
Stefan Schliebs, Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Personalized information modeling for personalized medicine
Yingjie Hu, Nikola Kasabov, Wen Liang
Springer Handbook of Bio Neuroinformatics, 2014
Ontologies and machine learning systems
Shoba Tegginmath, Russel Pears, Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Posterior distribution learning (PDL): A novel supervised learning framework
Enmei Tu, Jie Yang, Zhenghong Jia, Nicola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2014
EEG signal processing for brain-computer interfaces
Petia Georgieva, Filipe Silva, Mariofanna Milanova, Nikola Kasabov
Springer Handbook of Bio Neuroinformatics, 2014
Classification of fMRI data in the NeuCube evolving spiking neural network architecture
Norhanifah Murli, Nikola Kasabov, Bana Handaga
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2014
Information methods for predicting risk and outcome of stroke
Wen Liang, Rita Krishnamurthi, Nikola Kasabov, Valery Feigin
Springer Handbook of Bio Neuroinformatics, 2014
Medical image enhancement based on shearlet transform and unsharp masking
Ayiguli Wubuli, Jia Zhen-Hong, Qin Xi-Zhong, Yang Jie, Nikola Kasabov
Journal of Medical Imaging and Health Informatics, 2014
White matter lesions change detection in MR images based on fuzzy nearness and non-subsampled shear waves
Li Ling-Ling, Jia Zhen-Hong, Qin Xi-Zhong, Yang Jie, Nikola Kasabov
Journal of Medical Imaging and Health Informatics, 2014
Unsupervised Segmentation Using Cluster Ensembles
Wei Zhang, Jie Yang, Wenjing Jia, Nikola Kasabov, Zhenhong Jia, Lei Zhou
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2014
Preface
2014 IEEE Conference on Evolving and Adaptive Intelligent Systems IEEE Eais 2014 Conference Proceedings, 2014
Geomagnetic storms can trigger stroke: Evidence from 6 large population-based studies in Europe and Australasia
Valery L. Feigin, Priya G. Parmar, Suzanne Barker-Collo, Derrick A. Bennett, Craig S. Anderson, Amanda G. Thrift, Birgitta Stegmayr, Peter M. Rothwell, Maurice Giroud, Yannick Bejot, Phillip Carvil, Rita Krishnamurthi, Nikola Kasabov
Stroke, 2014
NeuCube neuromorphic framework for spatio-temporal brain data and its Python implementation
Nathan Scott, Nikola Kasabov, Giacomo Indiveri
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Spiking neural network for on-line cognitive activity classification based on EEG data
Stefan Schliebs, Elisa Capecci, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
NeuCubeRehab: A pilot study for EEG classification in rehabilitation practice based on spiking neural networks
Yixiong Chen, Jin Hu, Nikola Kasabov, Zengguang Hou, Long Cheng
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Spatio-temporal EEG data classification in the NeuCube 3D SNN environment: Methodology and examples
Nikola Kasabov, Jin Hu, Yixiong Chen, Nathan Scott, Yulia Turkova
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Salient object segmentation based on automatic labeling
Lei Zhou, Chen Gong, YiJun Li, Yu Qiao, Jie Yang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Evolving spiking neural network-a survey
Stefan Schliebs, Nikola Kasabov
Evolving Systems, 2013
Evolving integrated multi-model framework for on line multiple time series prediction
Russel Pears, Harya Widiputra, Nikola Kasabov
Evolving Systems, 2013
Training spiking neural networks to associate spatio-temporal input-output spike patterns
Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola Kasabov
Neurocomputing, 2013
Brain-like system for audiovisual person authentication based on time-to-first spike coding
Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov
IT Policy and Ethics Concepts Methodologies Tools and Applications, 2013
Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition
Nikola Kasabov, Kshitij Dhoble, Nuttapod Nuntalid, Giacomo Indiveri
Neural Networks, 2013
Neurocomputing for spatio/spectro-temporal pattern recognition and early event prediction: Methods, systems, applications
Communications in Computer and Information Science, 2013
The evolution of the evolving neuro-fuzzy systems: From expert systems to spiking-, neurogenetic-, and quantum inspired
Nikola Kasabov
Studies in Fuzziness and Soft Computing, 2013
Special Issue: Contemporary development of neural computation and applications
Ivan Jordanov, Bruno Apolloni, Nikola Kasabov
Neural Computing and Applications, 2013
Towards a Wearable Coach: Classifying Sports Activities with Reservoir Computing
Stefan Schliebs, Nikola Kasabov, Dave Parry, Doug Hunt
Communications in Computer and Information Science, 2013
An experimental comparison of semi-supervised learning algorithms for multispectral image classification
Enmei Tu, Jie Yang, Jiangxiong Fang, Zhenghong Jia, Nikola Kasabov
Photogrammetric Engineering and Remote Sensing, 2013
Analysis of lip motion change arising as a result of amusement feeling
Yoichi Kageyama, Atsushi Momose, Tsuyoshi Takahashi, Masaki Ishii, Makoto Nishida, Ammar Mohemmed, Nikola Kasabov
Ieej Transactions on Electrical and Electronic Engineering, 2013
Modelling the effect of genes on the dynamics of probabilistic spiking neural networks for computational neurogenetic modelling
Nikola Kasabov, Stefan Schliebs, Ammar Mohemmed
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2012
Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition
Nikola Kasabov
Is 2012 2012 6th IEEE International Conference Intelligent Systems Proceedings, 2012
Evaluating SPAN incremental learning for handwritten digit recognition
Ammar Mohemmed, Guoyu Lu, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2012
NeuCube EvoSpike architecture for spatio-temporal modelling and pattern recognition of brain signals
Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2012
Dynamic learning of multiple time series in a nonstationary environment
Harya Widiputra, Russel Pears, Nikola Kasabov
Learning in Non Stationary Environments Methods and Applications, 2012
Incremental learning algorithm for spatio-temporal spike pattern classification
Ammar Mohemmed, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2012
Online spatio-temporal pattern recognition with evolving spiking neural networks utilising address event representation, rank order, and temporal spike learning
Kshitij Dhoble, Nuttapod Nuntalid, Giacomo Indiveri, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2012
Evolving spiking neural networks and neurogenetic systems for spatio- and spectro-temporal data modelling and pattern recognition
Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2012
Preface
Plamen Angelov, Dimitar Filev, Nik Kasabov, José Antonio Iglesias
2012 IEEE Conference on Evolving and Adaptive Intelligent Systems Eais 2012 Proceedings, 2012
Span: Spike pattern association neuron for learning spatio-temporal spike patterns
AMMAR MOHEMMED, STEFAN SCHLIEBS, SATOSHI MATSUDA, NIKOLA KASABOV
International Journal of Neural Systems, 2012
LDA merging and splitting with applications to multiagent cooperative learning and system alteration
Shaoning Pang, Tao Ban, Y. Kadobayashi, N. K. Kasabov
IEEE Transactions on Systems Man and Cybernetics Part B Cybernetics, 2012
Constructing robust liquid state machines to process highly variable data streams
Stefan Schliebs, Maurizio Fiasché, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2012
Brain-like system for audiovisual person authentication based on time-to-first spike coding
Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov
Computational Modeling and Simulation of Intellect Current State and Future Perspectives, 2011
Probabilistic computational neurogenetic modeling: From cognitive systems to alzheimer's disease
Nikola Kasabov, Reinhard Schliebs, Hiroshi Kojima
IEEE Transactions on Autonomous Mental Development, 2011
Guest editorial special issue on computational modeling of neural and brain development
Yaochu Jin, Yan Meng, Juyang Weng, Nikola Kasabov
IEEE Transactions on Autonomous Mental Development, 2011
Statistical approaches to automatic level set image segmentation with multiple regions
Jie Yang
Optical Engineering, 2011
Personalised modelling on SNPs data for Crohn's disease prediction
Yingjie Hu, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
SPAN: A neuron for precise-time spike pattern association
Ammar Mohemmed, Stefan Schliebs, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Reservoir-based evolving spiking neural network for spatio-temporal pattern recognition
Stefan Schliebs, Haza Nuzly Abdull Hamed, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
EEG classification with BSA spike encoding algorithm and evolving probabilistic spiking neural network
Nuttapod Nuntalid, Kshitij Dhoble, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Exploring associations between changes in ambient temperature and stroke occurrence: Comparative analysis using global and personalised modelling approaches
Wen Liang, Yingjie Hu, Nikola Kasabov, Valery Feigin
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Evolving probabilistic spiking neural networks for spatio-temporal pattern recognition: A preliminary study on moving object recognition
Nikola Kasabov, Kshitij Dhoble, Nuttapod Nuntalid, Ammar Mohemmed
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Correlation-aided support vector regression for forex time series prediction
Shaoning Pang, Lei Song, Nik Kasabov
Neural Computing and Applications, 2011
Are probabilistic spiking neural networks suitable for reservoir computing?
Stefan Schliebs, Ammar Mohemmed, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2011
An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification
Haza Nuzly Abdull Hamed, Nikola Kasabov, Siti Mariyam Shamsuddin, Harya Widiputra, Kshitij Dhoble
Proceedings of the International Joint Conference on Neural Networks, 2011
Quantum-inspired particle swarm optimisation for integrated feature and parameter optimisation of evolving spiking neural networks
International Journal of Artificial Intelligence, 2011
Special issue on swarm intelligence algorithms and applications
International Journal of Artificial Intelligence, 2011
Personalized mode transductive spanning SVM classification tree
Shaoning Pang, Tao Ban, Youki Kadobayashi, Nikola Kasabov
Information Sciences, 2011
Multilayer level set method for multiregion image segmentation
Jie Yang
Optical Engineering, 2011
Efficient multiresolution level set image segmentation with multiple regions
Jie Yang
Optical Engineering, 2011
Kalman filter to estimate dynamic and important patterns of interaction between multiple variables
Kalman Filtering, 2011
Dynamic interaction networks versus local trend models for multiple time-series prediction
Harya Widiputra, Russel Pears, Nikola Kasabov
Cybernetics and Systems, 2011
Prediction of preeclampsia and delivery of small for gestational age babies based on a combination of clinical risk factors in high-risk women
Paul T. Seed, Lucy C. Chappell, Michael A. Black, Katrina K. Poppe, Yuan-Chun Hwang, Nikola Kasabov, Lesley McCowan, Andrew H. Shennan, Steven H. Wu, Lucilla Poston, Robyn A. North
Hypertension in Pregnancy, 2011
Multiple time-series prediction through multiple time-series relationships profiling and clustered recurring trends
Harya Widiputra, Russel Pears, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2011
Method for training a spiking neuron to associate input-output spike trains
Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola Kasabov
IFIP Advances in Information and Communication Technology, 2011
Narrow band multi-region level set method for remote sensing image
Guang Pu Xue Yu Guang Pu Fen Xi Spectroscopy and Spectral Analysis, 2011
Optimization of Spiking Neural Networks with dynamic synapses for spike sequence generation using PSO
Ammar Mohemmed, Satoshi Matsuda, Stefan Schliebs, Kshitij Dhoble, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2011
Towards spatio-temporal pattern recognition using evolving spiking neural networks
Stefan Schliebs, Nuttapod Nuntalid, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2010
Tuning N-gram string kernel SVMs via meta learning
Nuwan Gunasekara, Shaoning Pang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2010
Factorizing class characteristics via group MEBs construction
Ye Chen, Shaoning Pang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2010
A biologically inspired evolving spiking neural model with rank-order population coding and a taste recognition system case study
S. Soltic, N. Kasabov
System and Circuit Design for Biologically Inspired Intelligent Learning, 2010
Knowledge extraction from evolving spiking neural networks with rank order population coding
SNJEZANA SOLTIC, NIKOLA KASABOV
International Journal of Neural Systems, 2010
Evolving intelligent systems
Proceedings of the International Symposium on Evolving Intelligent Systems A Symposium at the Aisb 2010 Convention, 2010
Preface EIS -10
Proceedings of the International Symposium on Evolving Intelligent Systems A Symposium at the Aisb 2010 Convention, 2010
On the probabilistic optimization of spiking neural networks
STEFAN SCHLIEBS, NIKOLA KASABOV, MICHAËL DEFOIN-PLATEL
International Journal of Neural Systems, 2010
International Journal of Neural Systems: Introduction
International Journal of Neural Systems, 2010
Evolving spiking neural networks for audiovisual information processing
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasabov
Neural Networks, 2010
Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems
Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Nikola Kasabov
Evolving Systems, 2010
Longitudinal study of a 9p21.3 SNP using a national electronic healthcare database
Patrick Gladding, John Mackay, Mark Webster, Harvey White, Katrina Ellis, Mildred Lee, Nikola Kasabov, Ralph Stewart
Personalized Medicine, 2010
Online feature extraction for evolving intelligent systems
S. Ozawa, S. Pang, N. Kasabov
Evolving Intelligent Systems Methodology and Applications, 2010
Preface
Evolving Intelligent Systems Methodology and Applications, 2010
Evolving Intelligent Systems: Methodology and Applications
Evolving Intelligent Systems Methodology and Applications, 2010
Integrative probabilistic evolving spiking neural networks utilising quantum inspired evolutionary algorithm: A computational framework
Nikola Kasabov
Studies in Computational Intelligence, 2010
To spike or not to spike: A probabilistic spiking neuron model
Nikola Kasabov
Neural Networks, 2010
Integrated optimisation method for personalised modelling and case studies for medical decision support
Nikola Kasabov, Yingjie Hu
International Journal of Functional Informatics and Personalised Medicine, 2010
Analyzing the dynamics of the simultaneous feature and parameter optimization of an evolving spiking neural network
Stefan Schliebs, Michael Defoin-Platel, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2010
Incremental and decremental LDA learning with applications
Shaoning Pang, Tao Ban, Youki Kadobayashi, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2010
Coevolutionary method for gene selection and parameter optimization in microarray data analysis
Yingjie Hu, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Quantum-inspired evolutionary algorithm: A multimodel EDA
M.D. Platel, S. Schliebs, N. Kasabov
IEEE Transactions on Evolutionary Computation, 2009
Integrated feature selection and parameter optimization for evolving spiking neural networks using quantum inspired particle swarm optimization
Haza Nuzly Abdull Hamed, Nikola Kasabov, Siti Mariyam Shamsuddin
Socpar 2009 Soft Computing and Pattern Recognition, 2009
String pattern recognition using evolving spiking neural networks and quantum inspired particle swarm optimization
Haza Nuzly Abdull Hamed, Nikola Kasabov, Zbynek Michlovský, Siti Mariyam Shamsuddin
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Hierarchical core vector machines for network intrusion detection
Ye Chen, Shaoning Pang, Nikola Kasabov, Tao Ban, Youki Kadobayashi
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
String kernel based svm for internet security implementation
Zbynek Michlovský, Shaoning Pang, Nikola Kasabov, Tao Ban, Youki Kadobayashi
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
A novel evolving clustering algorithm with polynomial regression for chaotic time-series prediction
Harya Widiputra, Henry Kho, Lukas, Russel Pears, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Ontology based personalized modeling for type 2 diabetes risk analysis: An integrated approach
Anju Verma, Maurizio Fiasché, Maria Cuzzola, Pasquale Iacopino, Francesco C. Morabito, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Welcoming message from the president of INNS
Proceedings of the International Joint Conference on Neural Networks, 2009
Curiosity driven incremental LDA agent active learning
Shaoning Pang, Seiichi Ozawa, Nik Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2009
Quantum-inspired feature and parameter optimisation of evolving spiking neural networks with a case study from ecological modeling
Stefan Schliebs, Michael Defoin Platel, Sue Worner, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2009
Adaptive incremental principal component analysis in nonstationary online learning environments
Seiichi Ozawa, Yuki Kawashima, Shaoning Pang, Nikola Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2009
Integrative probabilistic evolving spiking neural networks utilising quantum inspired evolutionary algorithm: A computational framework
Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Personalized modeling based gene selection for microarray data analysis
Yingjie Hu, Qun Song, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Integrated feature and parameter optimization for an evolving spiking neural network
Stefan Schliebs, Michaël Defoin-Platel, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Personalised modelling for multiple time-series data prediction: A preliminary investigation in asia pacific stock market indexes movement
Harya Widiputra, Russel Pears, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Incremental principal component analysis based on adaptive accumulation ratio
Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Ontology based personalized modeling for chronic disease risk analysis: An integrated approach
Anju Verma, Nikola Kasabov, Elaine Rush, Qun Song
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Vision based mobile robot for indoor environmental security
Sean W. Gordon, Shaoning Pang, Ryota Nishioka, Nikola Kasabov, Takeshi Yamakawa
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
A novel incremental linear discriminant analysis for multitask pattern recognition problems
Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Shaoning Pang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems, ESDIS 2009 - Proceedings: Welcome Message
2009 IEEE Workshop on Evolving and Self Developing Intelligent Systems Esdis 2009 Proceedings, 2009
An altered pattern of circulating apolipoprotein E3 isoforms is implicated in preeclampsia
Kelly R. Atkinson, Marion Blumenstein, Michael A. Black, Steven H. Wu, Nikola Kasabov, Rennae S. Taylor, Garth J.S. Cooper, Robyn A. North
Journal of Lipid Research, 2009
Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models
Stefan Schliebs, Michaël Defoin-Platel, Sue Worner, Nikola Kasabov
Neural Networks, 2009
Soft computing methods for global, local and personalized modeling and applications in bioinformatics
Nikola Kasabov
Studies in Computational Intelligence, 2009
Integrative connectionist learning systems inspired by nature: Current models, future trends and challenges
Nikola Kasabov
Natural Computing, 2009
Encoding and decoding the knowledge of association rules over SVM classification trees
Shaoning Pang, Nikola Kasabov
Knowledge and Information Systems, 2009
Spanning SVM tree for personalized transductive learning
Shaoning Pang, Tao Ban, Youki Kadobayashi, Nik Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Discovering diagnostic gene targets and early diagnosis of acute GVHD using methods of computational intelligence over gene expression data
Maurizio Fiasché, Anju Verma, Maria Cuzzola, Pasquale Iacopino, Nikola Kasabov, Francesco C. Morabito
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2009
Guest editorial: Evolving fuzzy systems - Preface to the special section
Plamen Angelov, Dimitar Filev, Nikola Kasabov
IEEE Transactions on Fuzzy Systems, 2008
Incremental learning of chunk data for online pattern classification systems
S. Ozawa, S. Pang, N. Kasabov
IEEE Transactions on Neural Networks, 2008
An incremental principal component analysis based on dynamic accumulation ratio
Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang, Nikola Kasabov
Proceedings of the SICE Annual Conference, 2008
gSVMT: Aggregating SVMs over a dynamic grid learned from data
Shaoning Pang, Tao Ban, Youki Kadobayashi, Nik Kasabov
Proceedings of 11th International Conference on Computer and Information Technology Iccit 2008, 2008
Integrating local and personalised modelling with global ontology knowledge bases for biomedical and bioinformatics decision support
Nikola Kasabov, Qun Song, Lubica Benuskova, Paulo Gottgtroy, Vishal Jain, Anju Verma, Ilkka Havukkala, Elaine Rush, Russel Pears, Alex Tjahjana, Yingjie Hu, Stephen MacDonell
Studies in Computational Intelligence, 2008
R-SVMT: Discovering the knowledge of association rule over SVM classification trees
Shaoning Pang, Nik Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2008
Evolving spiking neural networks for taste recognition
S. Soltic, S. G. Wysoski, N. K. Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2008
Adaptive spiking neural networks for audiovisual pattern recognition
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2008
Ontology-based framework for personalized diagnosis and prognosis of cancer based on gene expression data
Yingjie Hu, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2008
Adaptive face recognition system using fast incremental principal component analysis
Seiichi Ozawa, Shaoning Pang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2008
Evolving connectionist systems for adaptive sport coaching
Boris Bacic, Nikola Kasabov, Stephen MacDonell, Shaoning Pang
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2008
Evolving intelligence in humans and machines: Integrative evolving connctionist systems approach
Nikola Kasabov
IEEE Computational Intelligence Magazine, 2008
Curiosity-driven multi-agent competitive and cooperative lda learning
International Journal of Innovative Computing Information and Control, 2008
Soft computing methods to predict gene regulatory networks: An integrative approach on time-series gene expression data
Zeke S.H. Chan, Ilkka Havukkala, Vishal Jain, Yingjie Hu, Nikola Kasabov
Applied Soft Computing Journal, 2008
Adaptive modeling and discovery in bioinformatics: The evolving connectionist approach
Nikola Kasabov
International Journal of Intelligent Systems, 2008
Bootstrapping Consistency Method for Optimal Gene Selection from Microarray Gene Expression Data for Classification Problems
Shaoning Pang, Ilkka Havukkala, Yingjie Hu, Nikola Kasabov
Machine Learning in Bioinformatics, 2008
On-line evolving fuzzy clustering
S. Shenbaga Devi, K. Vidhya
Proceedings International Conference on Computational Intelligence and Multimedia Applications Iccima 2007, 2008
Integrating evolving brain-gene ontology and connectionist-based system for modeling and knowledge discovery
Nikola Kasabov, Vishal Jain, Lubica Benuskova
Neural Networks, 2008
Evolving Connectionist System Based Role Allocation for Robotic Soccer
L. Huang, Q. Song, N. Kasabov
International Journal of Advanced Robotic Systems, 2008
Integration of brain-gene ontology and simulation systems for learning, modelling and discovery
Nik Kasabov, Vishal Jain, Lubica Benuskova, Paulo C. M. Gottgtroy, Frances Joseph
Studies in Computational Intelligence, 2008
SVMT-rule: Association rule mining over SVM classification trees
Shaoning Pang, Nik Kasabov
Studies in Computational Intelligence, 2008
Data mining, modeling and knowledge discovery methods for personalised biomedical decision support systems
N. Kasabov
Ifmbe Proceedings, 2008
Modeling brain dynamics using computational neurogenetic approach
Lubica Benuskova, Nikola Kasabov
Cognitive Neurodynamics, 2008
Fuzzy-neuro systems for local and personalized modelling
Nikola Kasabov, Qun Song, Tian Min Ma
Studies in Fuzziness and Soft Computing, 2008
MUFIS: A neuro-fuzzy inference system using multiple types of fuzzy rules
Yuan-Chun Hwang, Qun Song, Nikola Kasabov
IEEE International Conference on Fuzzy Systems, 2008
Fast and adaptive network of spiking neurons for multi-view visual pattern recognition
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasabov
Neurocomputing, 2008
Evolving connectionist systems: The knowledge engineering approach
Evolving Connectionist Systems the Knowledge Engineering Approach Second Edition, 2007
A versatile quantum-inspired evolutionary algorithm
Michael Defoin Platel, Stefan Schliebs, Nikola Kasabov
2007 IEEE Congress on Evolutionary Computation CEC 2007, 2007
A semi-online training algorithm for the radial basis function neural networks: Applications to bankruptcy prediction in banks
Vadlamani Ravi, P. Ravi Kumar, Eruku Ravi Srinivas, Nikola K. Kasabov
Advances in Banking Technology and Management Impacts of ICT and CRM, 2007
Welcome from HIS 2007 organizers
Proceedings 7th International Conference on Hybrid Intelligent Systems His 2007, 2007
Brain gene ontology (BGO): Tool to facilitate education and research in neuroinformatics area
Proceedings of Nzcsrsc 2007 the 5th New Zealand Computer Science Research Student Conference, 2007
Evolving brain-gene ontology system (EBGOS): Towards integrating bioinformatics and neuroinformatics data to facilitate discoveries
Nikola Kasabov, Vishal Jain, Paulo C. M. Gottgtroy, Lubica Benuskova, Simei Gomes Wysoski, et al.
IEEE International Conference on Neural Networks Conference Proceedings, 2007
Classification consistency analysis for bootstrapping gene selection
Shaoning Pang, Ilkka Havukkala, Yingjie Hu, Nikola Kasabov
Neural Computing and Applications, 2007
Brain-, gene-, and quantum inspired computational intelligence: Challenges and opportunities
Nikola Kasabov
Studies in Computational Intelligence, 2007
Modeling L-LTP based on changes in concentration of pCREB transcription factor
Lubica Benuskova, Nikola Kasabov
Neurocomputing, 2007
Brain gene ontology and simulation system (BGOS) for a better understanding of the brain
Nikola Kasabov, Vishal Jain, Paulo C. M. Gottgtroy, Lubica Benuskova, Frances Joseph
Cybernetics and Systems, 2007
Global, local and personalised modeling and pattern discovery in bioinformatics: An integrated approach
Nikola Kasabov
Pattern Recognition Letters, 2007
Multiple gene expression classifiers from different array platforms predict poor prognosis of colorectal cancer
Yu-Hsin Lin, Jan Friederichs, Michael A. Black, Jörg Mages, Robert Rosenberg, Parry J. Guilford, Vicky Phillips, Mark Thompson-Fawcett, Nikola Kasabov, Tumi Toro, Arend E. Merrie, Andre van Rij, Han-Seung Yoon, John L. McCall, Jörg Rüdiger Siewert, Bernhard Holzmann, Anthony E. Reeve
Clinical Cancer Research, 2007
Bayesian learning of sparse gene regulatory networks
Zeke S.H. Chan, Lesley Collins, N. Kasabov
Biosystems, 2007
Text-independent speaker authentication with spiking neural networks
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2007
Brain-, gene-, and quantum-inspired computational intelligence: Challenges and opportunities
Nikola Kasabov
Computational Intelligence Theory and Applications International Conference 9th Fuzzy Days in Dortmund Germany Sept 18 20 2006 Proceedings, 2006
Brain-, gene-, and quantum-inspired computational intelligence: Challenges and opportunities
Advances in Soft Computing, 2006
Neuro-, genetic-, and quantum inspired evolving intelligent systems
Nikola Kasabov
Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems Efs 06, 2006
TWNFI - a transductive neuro-fuzzy inference system with weighted data normalization for personalized modeling
Qun Song, Nikola Kasabov
Neural Networks, 2006
Evolving intelligent systems: Methods, learning, & applications
Nikola Kasabov, Dimitar Filev
Proceedings of the 2006 International Symposium on Evolving Fuzzy Systems Efs 06, 2006
Chapter 21 Evolving ontologies for intelligent decision support
Paulo Gottgtroy, Nikola Kasabov, Stephen MacDonell
Capturing Intelligence, 2006
Welcome from the HIS-NCEI'06 chairs
Proceedings Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro Computing and Evolving Intelligence His Ncei 2006, 2006
Short-term ANN load forecasting from limited data using generalization learning strategies
Zeke S.H. Chan, H.W. Ngan, A.B. Rad, A.K. David, N. Kasabov
Neurocomputing, 2006
Estimating risk of events using SOM models: A case study on invasive species establishment
Muriel Gevrey, Sue Worner, Nikola Kasabov, Joel Pitt, Jean-Luc Giraudel
Ecological Modelling, 2006
Computational neurogenetic modelling: A pathway to new discoveries in genetic neuroscience
LUBICA BENUSKOVA, VISHAL JAIN, SIMEI G. WYSOSKI, NIKOLA K. KASABOV
International Journal of Neural Systems, 2006
Adaptation and interaction in dynamical systems: Modelling and rule discovery through evolving connectionist systems
Nikola Kasabov
Applied Soft Computing Journal, 2006
Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation
Qun Song, Nikola Kasabov, Tianmin Ma, Mark Roger Marshall
Artificial Intelligence in Medicine, 2006
Computational intelligence for bioinformatics: The knowledge engineering approach
Nikola Kasabov
Research and Development in Intelligent Systems Xxii Proceedings of AI 2005 the 25th Sgai International Conference on Innovative Techniques and Applications of Artificial Intelligence, 2006
Fast estimation of distribution algorithm (EDA) via constrained multi-parent recombination
Zeke S. H. Chan, N. Kasabov
Research and Development in Intelligent Systems Xxii Proceedings of AI 2005 the 25th Sgai International Conference on Innovative Techniques and Applications of Artificial Intelligence, 2006
Global em learning of finite mixture models using the Greedy elimination method
Zeke S. H. Chan, N. Kasabov
Research and Development in Intelligent Systems Xxii Proceedings of AI 2005 the 25th Sgai International Conference on Innovative Techniques and Applications of Artificial Intelligence, 2006
Investigating LLE eigenface on pose and face identification
Shaoning Pang, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
Transductive knowledge based fuzzy inference system for personalized modeling
Qun Song, Tianmin Ma, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
TTLSC - Transductive total least square model for classification and its application in medicine
Qun Song, Tian Min Ma, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
A two-stage methodology for gene regulatory network extraction from time-course gene expression data
Z CHAN, N KASABOV, L COLLINS
Expert Systems with Applications, 2006
An incremental principal component analysis for chunk data
S. Ozawa, Shaoning Pang, N. Kasabov
IEEE International Conference on Fuzzy Systems, 2006
Two-class SVM trees (2-SVMT) for biomarker data analysis
Shaoning Pang, Ilkka Havukkala, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
Computational neurogenetic modeling: A methodology to study gene interactions underlying neural oscillations
L. Benuskova, S.G. Wysoski, N. Kasabov
IEEE International Conference on Neural Networks Conference Proceedings, 2006
On-line learning with structural adaptation in a network of spiking neurons for visual pattern recognition
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
Adaptive learning procedure for a network of spiking neurons and visual pattern recognition
Simei Gomes Wysoski, Lubica Benuskova, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
An efficient greedy K-means algorithm for global gene trajectory clustering
Z CHAN, L COLLINS, N KASABOV
Expert Systems with Applications, 2006
Brain-gene ontology: Integrating bioinformatics and neuroinformatics data, information and knowledge to enable discoveries
Nikola Kasabov, Vishal Jain, Paulo C.M. Gottgtroy, Lubica Benuskova, Frances Joseph
Proceedings Sixth International Conference on Hybrid Intelligent Systems and Fourth Conference on Neuro Computing and Evolving Intelligence His Ncei 2006, 2006
Image and fractal information processing for large-scale chemoinformatics, genomics analyses and pattern discovery
Ilkka Havukkala, Lubica Benuskova, Shaoning Pang, Vishal Jain, Rene Kroon, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2006
Discovering rules of adaptation and interaction: From molecules and gene interaction to brain functions
Proceedings His 04 4th International Conference on Hybrid Intelligent Systems, 2005
A special issue on computational intelligence for bioinformatics
Nikola Kasabov, Ilkka Havukkala
Journal of Computational and Theoretical Nanoscience, 2005
Transductive modeling with GA parameter optimization
N. Mohan, N. Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2005
NFI: A neuro-fuzzy inference method for transductive reasoning
Qun Song, N.K. Kasabov
IEEE Transactions on Fuzzy Systems, 2005
Intelligent Agents and Multi-Agent Systems - 7th Pacific Rim International Workshop on Multi-Agents, PRIMA 2004, Revised Selected Papers: Preface
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
Computational intelligence, bioinformatics and computational biology: A brief overview of methods, problems and perspectives
Nikola Kasabov, Igor A. Sidorov, Dimiter S. Dimitrov
Journal of Computational and Theoretical Nanoscience, 2005
A computational neurogenetic model of a spiking neuron
N. Kasabov, L. Benuskova, S.G. Wysoski
Proceedings of the International Joint Conference on Neural Networks, 2005
Incremental learning in autonomous systems: Evolving connectionist systems for on-line image and speech recognition
N. Kasabov, D. Zhang, P.S. Pang
2005 IEEE Workshop on Advanced Robotics and Its Social Impacts, 2005
Evolving connectionist systems based role allocation of robots for soccer playing
L. Huang, Q. Song, N. Kasabov
Proceedings of the 20th IEEE International Symposium on Intelligent Control Isic 05 and the 13th Mediterranean Conference on Control and Automation MED 05, 2005
Artificial immune networks as a paradigm for classification and profiling of gene expression data
Diana Tsankova, Velichka Georgieva, Nikola Kasabov
Journal of Computational and Theoretical Nanoscience, 2005
Biologically plausible computational neurogenetic models: Modeling the interaction between genes, neurons and neural networks
Nikola Kasabov, Lubica Benuskova, Simei Gomes Wysoski
Journal of Computational and Theoretical Nanoscience, 2005
Classifying microRNAs by Gabor filter features from 2D structure bitmap images on a case study of human microRNAs
Ilkka Havukkala, Shaoning Pang, Vishal Jain, Nikola Kasabov
Journal of Computational and Theoretical Nanoscience, 2005
TWNFC - Transductive neural-fuzzy classifier with weighted data normalization and its application in medicine
Proceedings International Conference on Computational Intelligence for Modelling Control and Automation Cimca 2005 and International Conference on Intelligent Agents Web Technologies and Internet, 2005
Incremental learning for online face recognition
S. Ozawa, Soon Lee Toh, S. Abe, Shaoning Pang, N. Kasabov
Proceedings of the International Joint Conference on Neural Networks, 2005
Fast neural network ensemble learning via negative-correlation data correction
Z.S.H. Chan, N. Kasabov
IEEE Transactions on Neural Networks, 2005
Transductive knowledge based fuzzy inference system for personalized modeling
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science, 2005
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science): Preface
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science, 2005
An integrated feature selection and classification method to select minimum number of variables on the case study of gene expression data
LIANG GOH, NIKOLA KASABOV
Journal of Bioinformatics and Computational Biology, 2005
A hybrid genetic algorithm and expectation maximization method for global gene trajectory clustering
ZEKE S. H. CHAN, N. KASABOV, LESLEY COLLINS
Journal of Bioinformatics and Computational Biology, 2005
Incremental linear discriminant analysis for classification of data streams
S. Pang, S. Ozawa, N. Kasabov
IEEE Transactions on Systems Man and Cybernetics Part B Cybernetics, 2005
Incremental learning of feature space and classifier for face recognition
Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola Kasabov
Neural Networks, 2005
A preliminary study on negative correlation learning via Correlation-Corrected Data (NCCD)
ZEKE S. H. CHAN, NIKOLA KASABOV
Neural Processing Letters, 2005
International Journal of Neural Systems: Introduction
International Journal of Neural Systems, 2005
Computational neurogenetic modeling: Integration of spiking neural networks, gene networks, and signal processing techniques
Nikola Kasabov, Lubica Benuskova, Simei Gomes Wysoski
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2005
Chunk incremental LDA computing on data streams
Shaoning Pang, Seiichi Ozawa, Nikola Kasabov
Lecture Notes in Computer Science, 2005
Evolving connectionist system versus algebraic formulas for prediction of renal function from serum creatinine
Mark Roger Marshall, Qun Song, Tian Min Ma, Stephen Gerard Macdonell, Nikola Kirilov Kasabov
Kidney International, 2005
Efficient global clustering using the Greedy Elimination Method
Z.S.H. Chan, N. Kasabov
Electronics Letters, 2004
Bioinformatics: A knowledge engineering approach
2004 2nd International IEEE Conference Intelligent Systems Proceedings, 2004
WDN-RBF: Weighted data normalization for radial basic function type neural networks
Qun Song, N. Kasabov
IEEE International Conference on Neural Networks Conference Proceedings, 2004
Inductive vs transductive inference, global vs local models: SVM, TSVM, and SVMT for gene expression classification problems
Shaoning Pang, N. Kasabov
IEEE International Conference on Neural Networks Conference Proceedings, 2004
Gene trajectory clustering with a hybrid genetic algorithm and expectation maximization method
Z.S.H. Chan, N. Kasabov
IEEE International Conference on Neural Networks Conference Proceedings, 2004
Computational neurogenetic modeling: Integration of spiking neural networks, gene networks, and signal processing techniques
2004 IEEE International Workshop on Biomedical Circuits and Systems, 2004
Computational neurogenetic modelling: Gene networks within neural networks
N. Kasabov, L. Benuskova, S.G. Wysoski
IEEE International Conference on Neural Networks Conference Proceedings, 2004
A two-stage methodology for gene regulatory network extraction from time-course gene expression data
2004 IEEE International Workshop on Biomedical Circuits and Systems, 2004
Knowledge-based neural networks for gene expression data analysis, modelling and profile discovery
Nikola Kasabov
Drug Discovery Today Biosilico, 2004
Computational neurogenetics
Nikola Kasabov, Lubica Benuskova
Journal of Computational and Theoretical Nanoscience, 2004
TWRBF - Transductive RBF neural network with weighted data normalization
Qun Song, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
A modified incremental principal component analysis for on-line learning of feature space and classifier
Seiichi Ozawa, Shaoning Pang, Nikola Kasabov
Lecture Notes in Artificial Intelligence Subseries of Lecture Notes in Computer Science, 2004
One-pass incremental membership authentication by face classification
Shaoning Pang, Seiichi Ozawa, Nikola Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
An adaptive model of person identification combining speech and image information
D. Zhang, A. Ghobakhlou, N. Kasabov
2004 8th International Conference on Control Automation Robotics and Vision Icarcv, 2004
Gene regulatory network discovery from time-series gene expression Data - A computational intelligence approach
Nikola K. Kasabov, Zeke S. H. Chan, Vishal Jain, Igor Sidorov, Dimiter S. Dimitrov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Preface
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Dynamic neuro-fuzzy inference and statistical models for risk analysis of pest insect establishment
Snjezana Soltic, Shaoning Pang, Nikola Kasabov, Sue Worner, Lora Peackok
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2004
Transductive support vector machines and applications in bioinformatics for promoter recognition
N. Kasabov, Shaoning Pang
Proceedings of 2003 International Conference on Neural Networks and Signal Processing Icnnsp 03, 2003
An ontology engineering approach for knowledge discovery from data in evolving domains
Management Information Systems, 2003
Spoken language analysis, modeling and recognition - Statistical and adaptive connectionist approaches
Nikola Kasabov
Information Sciences, 2003
Reduced feature-set based parallel CHMM speech recognition systems
Waleed H. Abdulla, Nikola Kasabov
Information Sciences, 2003
Modeling the emergence of bilingual acoustic clusters: A preliminary case study
Mark Laws, Richard Kilgour, Nikola Kasabov
Information Sciences, 2003
Adaptive speech recognition with evolving connectionist systems
Akbar Ghobakhlou, Michael Watts, Nikola Kasabov
Information Sciences, 2003
Integrated Gene Expression Analysis of Multiple Microarray Data Sets Based on a Normalization Technique and on Adaptive Connectionist Model
Proceedings of the International Joint Conference on Neural Networks, 2003
Evolutionary Computation for Dynamic Parameter Optimisation of Evolving Connectionist Systems for On-line Prediction of Time Series with Changing Dynamics
Proceedings of the International Joint Conference on Neural Networks, 2003
Neural Systems for Solving the Inverse Problem of Recovering the Primary Signal Waveform in Potential Transformers
Proceedings of the International Joint Conference on Neural Networks, 2003
On-line pattern analysis by evolving self-organizing maps
Da Deng, Nikola Kasabov
Neurocomputing, 2003
Simulation of ECB decisions and forecast of short term Euro rate with an adaptive fuzzy expert system
Lorenzo Rizzi, Flavio Bazzana, Nikola Kasabov, Mario Fedrizzi, Luca Erzegovesi
European Journal of Operational Research, 2003
Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue
Matthias E Futschik, Anthony Reeve, Nikola Kasabov
Artificial Intelligence in Medicine, 2003
Prediction of clinical behaviour and treatment for cancers.
Applied Bioinformatics, 2003
An intelligent controller for automated operation of sequencing batch reactors
A. Cohen, D. Hegg, M. de Michele, Q. Song, N. Kasabov
Water Science and Technology, 2003
DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction
N.K. Kasabov, Qun Song
IEEE Transactions on Fuzzy Systems, 2002
Evolving connectionist systems for adaptive learning and knowledge discovery: Methods, tools, applications
N. Kasabov
Iconip 2002 Proceedings of the 9th International Conference on Neural Information Processing Computational Intelligence for the E Age, 2002
Evolving connectionist systems for adaptive learning and knowledge discovery: Methods, tools, applications
N. Kasabov
2002 1st International IEEE Symposium, 2002
A method for modelling genetic regulatory networks by using evolving connectionist systems and microarray gene expression data
N.K. Kasabov, D.S. Dimitrov
Iconip 2002 Proceedings of the 9th International Conference on Neural Information Processing Computational Intelligence for the E Age, 2002
Fuzzy clustering of gene expression data
IEEE International Conference on Plasma Science, 2002
GA-parameter optimisation of evolving connectionist systems for classification and a case study from bioinformatics
N. Kasabov, Qun Song
Iconip 2002 Proceedings of the 9th International Conference on Neural Information Processing Computational Intelligence for the E Age, 2002
Evolutionary optimisation of evolving connectionist systems
M. Watts, N. Kasabov
Proceedings of the 2002 Congress on Evolutionary Computation CEC 2002, 2002
Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning
N. Kasabov
IEEE Transactions on Systems Man and Cybernetics Part B Cybernetics, 2001
Ensembles of EFuNNs: An architecture for a multimodule classifier
IEEE International Conference on Fuzzy Systems, 2001
Knowledge based neural networks for on-line and off-line modeling and rule extraction
Proceedings of the Atlantic Symposium on Computational Biology and Genome Information Systems and Technolgoy Cbgist 2001, 2001
Artificial neural networks for intelligent information processing
Chemical Engineer, 2001
On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks
Nikola K. Kasabov
Neurocomputing, 2001
Dynamic optimisation of evolving connectionist system training parameters by pseudo-evolution strategy
Proceedings of the IEEE Conference on Evolutionary Computation ICEC, 2001
An evolving localised learning model for on-line image colour quantisation
IEEE International Conference on Image Processing, 2001
Channel Equalization Using Adaptive Filtering with Averaging
Proceedings of the Joint Conference on Information Sciences, 2000
Feature Selection for Parallel CHMM Speech Recognition Systems
Proceedings of the Joint Conference on Information Sciences, 2000
Modelling the emergence of speech sound categories in evolving connectionist systems
Proceedings of the Joint Conference on Information Sciences, 2000
Linear and non-linear pattern recognition models for classification of fruit from visible-near infrared spectra
Jaesoo Kim, Alistair Mowat, Philip Poole, Nikola Kasabov
Chemometrics and Intelligent Laboratory Systems, 2000
Evolving fuzzy neural network for camera operations recognition
L. Koprinska, N. Kasabov
Proceedings International Conference on Pattern Recognition, 2000
Simple evolving connectionist systems and experiments on isolated phoneme recognition
M. Watts, N. Kasabov
Proceedings of the 1st IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks, 2000
Hybrid system for robust recognition of noisy speech based on evolving fuzzy neural networks and adaptive filtering
N. Kasabov, G. Iliev
Proceedings of the International Joint Conference on Neural Networks, 2000
ESOM: An algorithm to evolve self-organizing maps from on-line data streams
Proceedings of the International Joint Conference on Neural Networks, 2000
AVIS: A connectionist-based framework for integrated auditory and visual information processing
Nikola Kasabov, Eric Postma, Jaap van den Herik
Information Sciences, 2000
HyFIS: Adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems
J. Kim, N. Kasabov
Neural Networks, 1999
From hybrid adjustable neuro-fuzzy systems to adaptive connectionist-based systems for phoneme and word recognition
N.K. Kasabov, R.I. Kilgour, S.J. Sinclair
Fuzzy Sets and Systems, 1999
Evolving connectionist systems: A theory and a case study on adaptive speech recognition
Proceedings of the International Joint Conference on Neural Networks, 1999
Adaptive blind noise suppression in some speech processing applications
G. Iliev, N. Kasabov
Iconip 1999 6th International Conference on Neural Information Processing Proceedings, 1999
Rule insertion and rule extraction from evolving fuzzy neural networks: algorithms and applications for building adaptive, intelligent expert systems
N. Kasabov, B. Woodford
IEEE International Conference on Fuzzy Systems, 1999
Enhancing recognition systems through an integrated processing of visual and audio information
Proceedings of the IEEE International Conference on Systems Man and Cybernetics, 1998
A fuzzy neural network for knowledge acquisition in complex time series
Control and Cybernetics, 1998
Rules of chaotic behaviour extracted from a fuzzy-neural network
R. Kozma, N.K. Kasabov
1998 IEEE International Conference on Fuzzy Systems Proceedings IEEE World Congress on Computational Intelligence, 1998
Hybrid intelligent adaptive systems: A framework and a case study on speech recognition
Nikola Kasabov, Robert Kozma
International Journal of Intelligent Systems, 1998
Phoneme-based speech recognition via fuzzy neural networks modeling and learning
N Kasabov
Information Sciences, 1998
Integration of connectionist methods and chaotic time-series analysis for the prediction of process data
R. Kozma, N. K. Kasabov, J. S. Kim, A. Cohen
International Journal of Intelligent Systems, 1998
Fuzzy rules extraction, reasoning and rules adaptation in fuzzy neural networks
N.K. Kasabov
IEEE International Conference on Neural Networks Conference Proceedings, 1997
Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks
N.K. Kasabov, M.J. Watts
IEEE International Conference on Neural Networks Conference Proceedings, 1997
Combining neuro-fuzzy and chaos methods for intelligent time series analysis - case study of heart rate variability
Proceedings of the IEEE International Conference on Systems Man and Cybernetics, 1997
Learning strategies for modular neuro-fuzzy systems: A case study on phoneme-based speech recognition
Nikola Kasabov
Journal of Intelligent and Fuzzy Systems, 1997
Special issue on advanced neuro-fuzzy techniques and their applications: introduction
Nikola Kasabov, Kaoru Hirota
Information Sciences, 1997
Statistical, connectionist, and fuzzy inference techniques for image classification
Steven A. Israel
Journal of Electronic Imaging, 1997
FuNN/2 - A fuzzy neural network architecture for adaptive learning and knowledge acquisition
Nikola K. Kasabov, Jaesoo Kim, Michael J. Watts, Andrew R. Gray
Information Sciences, 1997
Application of computational intelligence for on-line control of a sequencing batch reactor (SBR) at Morrinsville Sewage Treatment Plant
Water Science and Technology, 1997
Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems
Nikola K. Kasabov
Fuzzy Sets and Systems, 1996
Adaptable neuro production systems
Nikola K. Kasabov
Neurocomputing, 1996
Hybrid fuzzy connectionist rule-based systems and the role of fuzzy rules extraction
IEEE International Conference on Fuzzy Systems, 1995
Hybrid connectionist fuzzy systems for speech recognition and the use of connectionist production systems
Nikola K. Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 1995
Hybrid connectionist fuzzy production system: Towards building comprehensive ai
Nikola K. Kasabov
Intelligent Automation and Soft Computing, 1995
Hybrid systems for medical data analysis and decision making-a case study on varicose vein disorders
M. Bailey, C. Solomon, N. Kasabov, S. Greig
Proceedings 1995 2nd New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems Annes 1995, 1995
Model for exploiting associative matching in AI production systems
N.K. Kasabov, S.H. Lavington, S. Lin, C. Wang
Knowledge Based Systems, 1995
Hybrid systems for prediction-a case study of predicting effluent flow to a sewage plant
M. Bailey, N. Kasabov, T. Cohen, P. Mason, A. Gray
Proceedings 1995 2nd New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems Annes 1995, 1995
Intelligent human computer interfaces and the case study of building English-to-Maori talking dictionary
N. Kasabov, S. Sinclair, R. Kilgour, C. Watson, M. Laws, D. Kassabova
Proceedings 1995 2nd New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems Annes 1995, 1995
Connectionist fuzzy production systems
Nikola K. Kasabov
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 1994
Learning fuzzy rules through neural networks
N.K. Kasabov
Annes 1993 1st New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems, 1993
Connectionist expert systems
N.K. Kasabov, L.C. Jain
Annes 1993 1st New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems, 1993
A Connectionist Production System with Partial Match and its Use for Approximate Reasoning
NIKOLA K. KASABOV, STEPHAN I. SHISHKOV
Connection Science, 1993
Approximate reasoning with parallel connectionist production systems
Proceedings of the International Joint Conference on Neural Networks, 1993
Speech recognition based on Kohonen self-organizing feature maps and hybrid connectionist systems
N. Kasabov, D. Nikovski, E. Peev
Annes 1993 1st New Zealand International Two Stream Conference on Artificial Neural Networks and Expert Systems, 1993
A method for SIMD MIMD functionally reconfigurable multimicroprocessor systems design and parallel data exchange algorithms
Nikola K Kasabov
Parallel Computing, 1985
Functionally reconfigurable general purpose parallel machines and some image processing and pattern recognition applications
Nikola K Kasabov
Pattern Recognition Letters, 1985
Hierarchical discrete systems and realisation of parallel algorithms
N. K. Kasabov, G. T. Bijev, B. J. Jechev
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 1981

RECENT SCHOLAR PUBLICATIONS

eXCube2: Explainable Brain-Inspired Spiking Neural Network Framework for Emotion Recognition from Audio, Visual and Multimodal Audio–Visual Data
NK Kasabov, A Yang, Z Wang, I Abouhassan, A Kassabova, T Lappas
Biomimetics 11 (3), 208 , 2026
2026
Comparative performance analysis of quantum feature maps for quantum kernel-based machine learning
RK Jha, N Kasabov, S Bhattacharyya, D Coyle, G Prasad
Scientific Reports , 2026
2026
Brain-inspired Spiking Neural Network Frameworks for Multimodal Data Integration and Spatiotemporal Pattern Discovery: A Case Study on EEG-fMRI Data
N Shahab, M Doborjeh, N Kasabov
Available at SSRN 6381378 , 2026
2026
TSPFusion: Text-guided semantic perception for infrared and visible image fusion
X Qin, E Wang, S Zhou, B Wang, NK Kasabov
Infrared Physics & Technology, 106324 , 2025
2025
Citations: 3
A hybrid spiking neural network-quantum framework for spatio-temporal data classification: a case study on EEG data
RK Jha, N Kasabov, S Bhattacharyya, D Coyle, G Prasad
EPJ Quantum Technology 12 (1), 1-23 , 2025
2025
Citations: 3
Review of deep learning models with Spiking Neural Networks for modeling and analysis of multimodal neuroimaging data
A Khan, V Shim, J Fernandez, NK Kasabov, A Wang
Frontiers in Neuroscience 19, 1623497 , 2025
2025
Citations: 2
An Interpretable Framework of Spiking neural networks for Classification and Detection of Alzheimer's Disease Using Multimodal neuroimaging data
A Khan, V Shim, J Fernandez, N Kasabov, A Wang
Authorea Preprints , 2025
2025
Novel Neuron-Stability Weighted Dynamic Evolving Spiking Neural Network (NSW-DeSNN) for Classification of fMRI Data
M Doborjeh, Z Doborjeh, N Kasabov
International Conference on Neural Information Processing, 600-609 , 2025
2025
A Spiking Neural Network-Quantum Model for Spatiotemporal Data Analysis: An Experimental Framework
RK Jha, N Kasabov, S Bhattacharyya, D Coyle, G Prasad
2025 IEEE International Conference on Quantum Artificial Intelligence (QAI … , 2025
2025
Citations: 1
Genetic signatures predict social-cognitive trajectories in ultra-high-risk psychosis: A 24-month longitudinal study
Z Doborjeh, A Sumich, ON Medvedev, K Buchwald, M Doborjeh, B Singh, ...
Asian Journal of Psychiatry, 104749 , 2025
2025
SAIN: Search-And-INfer, a Mathematical and Computational Framework for Personalised Multimodal Data Modelling with Applications in Healthcare
CS Calude, P Gladding, A Henderson, N Kasabov
Algorithms 18 (10), 605 , 2025
2025
SAIN: Search-And-INfer, A Mathematical and Computational Framework for Personalised Multimodal Data Modelling with Applications in Health Care
N Kasabov, C Calude, A Henderson, P Gladding
2025
NEuroMOrphic Neural-Response Decoding System for Adaptive and Personalized Neuro-Prosthetics’ Control
G Rusev, S Yordanov, S Nedelcheva, A Banderov, H Lafaye de Micheaux, ...
Biomimetics 10 (8), 518 , 2025
2025
Citations: 1
A multispectral pansharpening method based on CNN-DI network with mixture of experts
Z Guo, J Lei, S Zhou, B Wang, NK Kasabov
Applied Soft Computing, 113499 , 2025
2025
Genetic Predictors of Social and Cognitive Outcomes in People with Ultra-High-Risk of Psychosis Using Spiking Neural Networks
Z Doborjeh, B Singh, A Sumich, M Doborjeh, WWB Goh, N Kasabov
2025 International Joint Conference on Neural Networks (IJCNN), 1-7 , 2025
2025
Modeling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach
M Hafezi Fard, K Petrova, NK Kasabov, GY Wang
Big Data and Cognitive Computing 9 (7), 173 , 2025
2025
Machine learning-guided high-definition transcranial direct current stimulation prevents cybersickness
AHX Yang, C Galán-Augé, NK Kasabov, YO Cakmak
Virtual reality 29 (3), 94 , 2025
2025
Citations: 2
Spiking neural networks for multimodal neuroimaging: A comprehensive review of current trends and the NeuCube brain-inspired architecture
O Garcia-Palencia, J Fernandez, V Shim, NK Kasabov, A Wang, ...
Bioengineering 12 (6), 628 , 2025
2025
Citations: 12
LarTap: A Luminance-Aware Framework With Text-Correlation Priors for Multi-Exposure Image Fusion
E Wang, J Li, T Yan, J Lei, S Zhou, B Wang, J Liu, NK Kasabov
IEEE Transactions on Circuits and Systems for Video Technology , 2025
2025
Citations: 1
Modelling the Effect of Prior Knowledge on Memory Efficiency for the Study of Transfer of Learning: A Spiking Neural Network Approach
K Petrova, N Kasabov, GY Wang
2025

MOST CITED SCHOLAR PUBLICATIONS

Foundations of neural networks, fuzzy systems, and knowledge engineering
NK Kasabov
Marcel Alencar , 1996
1996
Citations: 1781
DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction
NK Kasabov, Q Song
IEEE transactions on Fuzzy Systems 10 (2), 144-154 , 2002
2002
Citations: 1617
Evolving connectionist systems: the knowledge engineering approach
N Kasabov
Springer London , 2007
2007
Citations: 932
Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning
N Kasabov
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 31 … , 2001
2001
Citations: 632
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
NK Kasabov
Neural networks 52, 62-76 , 2014
2014
Citations: 592
Dynamic evolving spiking neural networks for on-line spatio-and spectro-temporal pattern recognition
N Kasabov, K Dhoble, N Nuntalid, G Indiveri
Neural Networks 41, 188-201 , 2013
2013
Citations: 488
HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems
J Kim, N Kasabov
Neural networks 12 (9), 1301-1319 , 1999
1999
Citations: 488
Artificial intelligence: a systematic review of methods and applications in hospitality and tourism
Z Doborjeh, N Hemmington, M Doborjeh, N Kasabov
International journal of contemporary hospitality management 34 (3), 1154-1176 , 2022
2022
Citations: 480
Incremental linear discriminant analysis for classification of data streams
S Pang, S Ozawa, N Kasabov
IEEE transactions on Systems, Man, and Cybernetics, part B (Cybernetics) 35 … , 2005
2005
Citations: 446
Spiking neural networks and online learning: An overview and perspectives
JL Lobo, J Del Ser, A Bifet, N Kasabov
Neural Networks 121, 88-100 , 2020
2020
Citations: 427
Evolving intelligent systems: methodology and applications
P Angelov, DP Filev, N Kasabov
John Wiley & Sons , 2010
2010
Citations: 416
Time-space, spiking neural networks and brain-inspired artificial intelligence
NK Kasabov
Springer , 2019
2019
Citations: 400
Span: Spike pattern association neuron for learning spatio-temporal spike patterns
A Mohemmed, S Schliebs, S Matsuda, N Kasabov
International journal of neural systems 22 (04), 1250012 , 2012
2012
Citations: 349
Evolving Fuzzy Neural Networks-Algorithms, Applications and Biological
N Kasabov
Methodologies For The Conception, Design And Application Of Soft Computing … , 1998
1998
Citations: 290
Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems
NK Kasabov
Fuzzy sets and Systems 82 (2), 135-149 , 1996
1996
Citations: 231
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications
N Kasabov, NM Scott, E Tu, S Marks, N Sengupta, E Capecci, M Othman, ...
Neural Networks 78, 1-14 , 2016
2016
Citations: 219
Evolving spiking neural network—a survey
S Schliebs, N Kasabov
Evolving Systems 4 (2), 87-98 , 2013
2013
Citations: 217
Quantum-inspired evolutionary algorithm: A multimodel EDA
MD Platel, S Schliebs, N Kasabov
IEEE Transactions on Evolutionary Computation 13 (6), 1218-1232 , 2008
2008
Citations: 209
Evolving spiking neural networks for audiovisual information processing
SG Wysoski, L Benuskova, N Kasabov
Neural Networks 23 (7), 819-835 , 2010
2010
Citations: 205
To spike or not to spike: A probabilistic spiking neuron model
N Kasabov
Neural Networks 23 (1), 16-19 , 2010
2010
Citations: 202

GRANT DETAILS

Research Grants
(1) Principal Investigator or Associate Principal Investigator
• 2022-2025, NEMO-BMI, EU funded project in Collaboration b etwwen France, Bulgaria, the Netherlands and Switzerland, 3.4mln Euros.
 2020-2023, MBIE-Singapore Data Science Fund: Computaionla neurgenetic modelling for mental health, 2.2mln NZD
 2015-2019, EU funded project PANTHER, including: Poland, Hungary, Spain, Ireland, France, Australia and New Zealand, NZD 2.8mln,
 2017-2019, MBIE Advanced technologies for convective weather prediction (with Met Ocean Solution and Services), 500,000.
 2015-2019, AUT Strategic Investment Research Fund (SRIF), 650,000; INTELLECTE: Intelligent Information Technologies for Innovation, Interaction and Creativity in Complex Data Modelling and Decision Support
 2011-2019, Ministry of Education, NZ, Tripartite project with China: Advanced information technologies for environmental event prediction; 120,000NZD
 2012-2015, MBIE, Advanced spiking neural network technologies for neurorehabilitation, 300,000NZD
 2011-2012, EU FP7 Marie Curie EvoSpike project,; INI/ETH and University of Zurich, Euro120,000; (with G.Indiveri)
 2008/2010, NiCT, Tokyo, Japan, Fast algorithms for cyber-security data stream on-line modelling and analysis

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

(h) Computational Platforms and Software – Designed, Developed and Published
1. N.Kasabov et al, NeuCube – a spiking neural network spatio-temporal data machine, KEDRI, 2013-2021 implemented in different versions:
(a) Matlab version: and
(b) Python version (Balkaran Singh)
(c) Version to work on SpiNNaker (Behrenbeck): .
(d) NeuCube visualisation as a brain-inspired mode:
2. N.Kasabov et al, NeuroGeMS:
3. N.Kasabov et al, EvoSpike - a spiking neural network software environment for modelling spatio-temporal data, 2013:
Patents
1. N.Kasabov, V.Feigin, Z.Hou, Y.Chen, Improved method and system for predicting outcomes based on spatio/spectro-temporal data, PCT patent WO2015/030606 A2, US2016/0210552 A1. Granted/Publication date: 21 July 2016.
2. N.Kasabov, Data Analysis and Predictive Systems and Related Methodologies, US patent 9,002,682 B2, 7 April 2015.
3. R. North, M. Blumenstein, M. McMaster, N. Kasabov, M. Black, G. Cooper, L. McCowan, Biomarkers for prediction of preeclampsia and/or cardiovascular disease, PCT, WO2009/108073A1, 27.02.2009.
4. N.Kasabov, M. Futschik, M.Sullivan, A.Reeve, Method and Medical Decision Support System Utilizing Gene Expression

CONSULTANCY

Pacific Edge Biotechnology Ltd; FONTERRA; National Centre for
Bioprotection – Lincoln; Telecom New Zealand; University of Otago; AUT; The University of Auckland; .

Industry, Institute, or Organisation Collaboration

• MBIE funded project on Data Science NZ-Singapore, 2020-2023.
• EU funded project PANTHER, including: Poland, Hungary, Spain, Ireland, France, Australia and New Zealand, 2015-2019.
• Tripartite collaboration: Shanghai Jiao Tong University – Xinjiang University – AUT – coordinator, since 2009.
• Collaboration project with the Chinese Academy of Sciences – Institute of Automation – coordinator, since 2010.
• Partnership with several European Universities for EU projects: ETH Zurich; U. Manchester; Humboldt U., since 2011.
• Collaboration with Kyushu Institute of Technology, Japan, since 1993.
• Collaboration with the National Institute of Commun. and Information Technologies, NiCT, Tokyo, Japan, 2007-2011.
• PI of a collaborative research project “Connectionist-based intelligent information systems”, FRST/NERF NZ, 1995-2007.
• Research associate and consultant: Advanced Information Modelling Joint Venture, AUT and James and Wells, Chief Scientist, since 2011; Pacific Edge Biotechnology Ltd. - PEBL NZ, Co-founder and consultant, since 1998; NZ Bio-protection CoRE - Centre of Research Excellence, Lincoln, consultant, since 2003; SCOPE Project – U. Auckland, consultant, 2004-2009; RASP project – U. Auckland, consultant, 2008.
• Director, NZ Bioinformatics Summer School at AUT University, 2003 and 2004.
• Coordinator of SIG “Computational Intelligence in Bioinformatics” as part of BISC (Berkeley Initiative of Soft Computing), Department of and

INDUSTRY EXPERIENCE

• Co-founder: Pacific Edge Biotechnology Ltd (Dunedin);
• Director: Knowledge Engineering Consulting Ltd (Auckland).
• Application oriented projects and consultation work for: Fonterra; Telecom New Zealand; ViaLactia; Goat Ventures; CRI: Hort Researc; AgResearch; Food and Crop; Auckland DHBs, and others.

STARTUP

KECL, Https://

SOCIAL, ECONOMIC, or ACADEMIC BENEFITS

Commercial benefit has been gained by the commercial partners and the end users of my
Projects as listed above. Most of the 50 PhD students, supervised by me have joined New Zealand companies and are contributing to the commercial success of the companies. Social benefits have been gained through the creation and the implementation of new information technologies as a result of my research projects that have benefited the New Zealand ICT sector and New Zealand as a whole. Environmental impact has also been achieved through the work with the Centre for Bioprotection for harmful species establishment prediction and with GNS Science on seismic data modelling