Chiranji Lal Chowdhary

Scopus Publications

PCE-FL: A Personalized, Clustered, and Communication-Efficient Federated Learning Framework for Robust Tomato Leaf Disease Detection
Pradeep Gupta, Sonam Gupta, Lipika Goel, Abhay Kumar Agarwal, Arjun Singh, Vijay Shankar Sharma, Chiranji Lal Chowdhary, Ruchita Chowdhary
Agriengineering, 2026
Tomato leaf diseases represent a persistent threat to global food security, causing annual crop losses of 20% to 40%. Although deep learning models achieve accuracies exceeding 95% in centralized settings, their deployment across distributed farms is constrained by data privacy concerns, communication bottlenecks, and heterogeneous data quality. This paper proposes Personalized, Clustered, and Communication-Efficient Federated Learning (PCE-FL), a framework that integrates three synergistic components: (1) server-side client clustering to group farms with similar data distributions for personalized model training; (2) federated knowledge distillation to reduce communication overhead by over 91%; and (3) reputation-based aggregation to ensure robustness against unreliable contributions. Extensive experiments on realistic non-IID simulations of the PlantVillage tomato dataset Dirichlet(α∈{1.0,0.5,0.1}) demonstrate that PCE-FL achieves 89.1% accuracy under extreme heterogeneity (α=0.1), surpassing FedAvg by 10.9 and IFCA by 4.8 percentage points, while maintaining a 91% reduction in communication cost. All improvements are statistically significant (p<0.001). These results advance the practical deployment of privacy-preserving collaborative AI in resource-constrained agricultural environments.
Integrating feature fusion with hybrid optimization for multiple sclerosis MRI classification
Nandini Anam, Sharief Basha S, Chiranji Lal Chowdhary
Array, 2026
Detecting Multiple Sclerosis (MS) has previously been difficult to identify with MRI scans due to the subtlety and dispersion of lesions, as well as other imaging anomalies. The researchers in this study created a unique hybrid framework that combines two state-of-the-art convolutional neural networks, ResNet-50 and EfficientNet-B7. Additionally, a new hybrid bio-inspired optimisation strategy combining the Grey Wolf Optimiser (GWO) and the Genetic Algorithm (GA) is described. The technique simplifies the computations and ensures that the best characteristics are picked. We extracted deep features from both CNNs, used Principal Component Analysis (PCA) to reduce them to high dimensions, and then employed the GA-GWO method to identify suitable features. The enhanced artificial neural network (ANN) classifier outperformed standalone CNN-based models, achieving a maximum accuracy of 90.67%(refer to table 4). The suggested framework for dependable and comprehensible precision and processing efficacy. This work has the potential to motivate future studies in related areas.
Federated Learning Approaches for Predicting and Modelling Brain Stroke Lesion Progression : A Review
Adhi Siva M, Chiranji Lal Chowdhary
Archives of Computational Methods in Engineering, 2026
Hybrid deep learning and feature optimization approach for early detection of multiple sclerosis
Nandini Anam, Sharief Basha S., Chiranji Lal Chowdhary
Frontiers in Human Neuroscience, 2026
The healthcare field increasingly relies on autonomous systems for the detection and analysis of Multiple Sclerosis (MS) to minimize diagnostic delays, resource burdens, reduce the progression of disability, and enhance clinical decision-making efficiency. Such systems ensure accurate and timely treatment, ultimately improved patient outcomes. In this study, a hybrid framework combining deep learning-based feature extraction, metaheuristic feature selection, and machine learning (ML) classifiers is proposed for accurate MS classification. All MRI images were preprocessed using Contrast Limited Adaptive Histogram Equalization (CLAHE), resizing, and normalization to enhance contrast and standardize the input dimensions. Deep features were extracted using the pretrained VGG16 convolutional neural network (CNN), in which the fully connected layers were removed, and the convolutional base was used to obtain high-dimensional features per image. To reduce dimensionality and improve classification performance, the Whale Optimization Algorithm (WOA) was employed to select the most discriminative subset of features using a Support Vector Machine (SVM)-based fitness function. Multiple classifiers were then trained and evaluated using the optimized feature set. Among them, the Artificial Neural Network integrated with WOA (ANN+WOA) achieved the highest classification accuracy of 98%, demonstrating the potential of the proposed model for reliable, efficient, and automated MS diagnosis.
MetaConstructs
Metaconstructs the Evolution of Digital Twins in the Metaverse Era, 2026
Hybrid feature optimized CNN for rice crop disease prediction
S. Vijayan, Chiranji Lal Chowdhary
Scientific Reports, 2025
The agricultural industry significantly relies on autonomous systems for detecting and analyzing rice diseases to minimize financial and resource losses, reduce yield reductions, improve processing efficiency, and ensure healthy crop production. Advances in deep learning have greatly enhanced disease diagnostic techniques in agriculture. Accurate identification of rice plant diseases is crucial to preventing the severe consequences these diseases can have on crop yield. Current methods often struggle with reliably diagnosing conditions and detecting issues in leaf images. Previously, leaf segmentation posed challenges, and while analyzing complex disease stages can be effective, it is computationally intensive. Therefore, segmentation methods need to be more accurate, cost-effective, and reliable. To address these challenges, we propose a hybrid bio-inspired algorithm, named the Hybrid WOA_APSO algorithm, which merges Adaptive Particle Swarm Optimization (APSO) with the Whale Optimization Algorithm (WOA). For disease classification in rice crops, we utilize a Convolutional Neural Network (CNN). Multiple experiments are conducted to evaluate the performance of the proposed model using benchmark datasets (Plantvillage), with a focus on feature extraction, segmentation, and preprocessing. Optimizing feature selection is a critical factor in enhancing the classification algorithm’s accuracy. We compare the accuracy, sensitivity, and specificity of our model against industry-standard techniques such as Support Vector Machine (SVM), Artificial Neural Network (ANN), and conventional CNN models. The experimental results indicate that the proposed hybrid approach achieves an impressive accuracy of 97.5% (Refer Table 8), which could inspire further research in this field.
Intelligent health model for medical imaging to guide laymen using neural cellular automata
Sandeep Kumar Sharma, Chiranji Lal Chowdhary, Vijay Shankar Sharma, Adil Rasool, Arfat Ahmad Khan
Scientific Reports, 2025
A layman in health systems is a person who doesn't have any knowledge about health data i.e., X-ray, MRI, CT scan, and health examination reports, etc. The motivation behind the proposed invention is to help laymen to make medical images understandable. The health model is trained using a neural network approach that analyses user health examination data; predicts the type and level of the disease and advises precaution to the user. Cellular Automata (CA) technology has been integrated with the neural networks to segment the medical image. The CA analyzes the medical images pixel by pixel and generates a robust threshold value which helps to efficiently segment the image and identify accurate abnormal spots from the medical image. The proposed method has been trained and experimented using 10000+ medical images which are taken from various open datasets. Various text analysis measures i.e., BLEU, ROUGE, and WER are used in the research to validate the produced report. The BLEU and ROUGE calculate a similarity to decide how the generated text report is closer to the original report. The BLEU and ROUGE scores of the experimented images are approximately 0.62 and 0.90, claims that the produced report is very close to the original report. The WER score 0.14, claims that the generated report contains the most relevant words. The overall summary of the proposed research is that it provides a fruitful medical report with accurate disease and precautions to the laymen.
Harnessing machine learning for academic insight: A study of educational performance in Bhopal, India
Vandana Onker, Krishna Kumar Singh, Hemraj Shobharam Lamkuche, Sunil Kumar, Vijay Shankar Sharma, Chiranji Lal Chowdhary, Vijay Kumar
Education and Information Technologies, 2025
Deep Learning Approach Towards Green IIOT
Harpreet Kaur Channi, Chiranji Lal Chowdhary
Studies in Computational Intelligence, 2025
Introduction to Industrial IoT and Smart Computing Techniques
Chiranji Lal Chowdhary, R. K. Nadesh, P. Kumaresan
Studies in Computational Intelligence, 2025
Preface
Studies in Computational Intelligence, 2025
NeuraPose: Effective Human Pose Detection Using Transfer Learning
Hardik Maheshwari, Varun Bhattacharya, Chiranji Lal Chowdhary
Lecture Notes in Networks and Systems, 2025
A Deep Cryptographic Framework for Securing the Healthcare Network from Penetration
Arjun Singh, Vijay Shankar Sharma, Shakila Basheer, Chiranji Lal Chowdhary
Sensors, 2024
Machine learning for mobile communications
Sinh Cong Lam, Chiranji Lal Chowdhary, Tushar Hrishikesh Jaware, Subrata Chowdhury
Machine Learning for Mobile Communications, 2024
Preface
Machine Learning for Mobile Communications, 2024
FedHealthFog: A federated learning-enabled approach towards healthcare analytics over fog computing platform
Subhranshu Sekhar Tripathy, Sujit Bebortta, Chiranji Lal Chowdhary, Tanmay Mukherjee, SeongKi Kim, Jana Shafi, Muhammad Fazal Ijaz
Heliyon, 2024
PrecisionLymphoNet: Advancing Malignant Lymphoma Diagnosis via Ensemble Transfer Learning with CNNs
Sivashankari Rajadurai, Kumaresan Perumal, Muhammad Fazal Ijaz, Chiranji Lal Chowdhary
Diagnostics, 2024
Preface
Metaverse for the Healthcare Industry, 2024
Introduction
Enhancing Steganography Through Deep Learning Approaches, 2024
Conclusion
Enhancing Steganography Through Deep Learning Approaches, 2024
The Metaverse for the Healthcare Industry
Chowdhary, Chiranji Lal
Metaverse for the Healthcare Industry, 2024
The Role of Deep Learning Innovations With CNNs and GANs in Steganography
Harpreet Kaur, Chiranji Lal Chowdhary
Enhancing Steganography Through Deep Learning Approaches, 2024
Challenges, Ethics, and Limitations of the Metaverse for the Health-Care Industry
Chiranji Lal Chowdhary, Abhishek Ranjan
Metaverse for the Healthcare Industry, 2024
Deep Learning-Based Steganography for Smart Agriculture
Chiranji Lal Chowdhary, S. Vijayan
Enhancing Steganography Through Deep Learning Approaches, 2024
Deep Learning for Skin Cancer Detection: Insights and Applications
S. Rajeshkumar, Chiranji Lal Chowdhary
Enhancing Steganography Through Deep Learning Approaches, 2024
Fundamentals of the Metaverse for the Healthcare Industry
Chiranji Lal Chowdhary, Siva Rama Krishnan Somayaji, Vijay Kumar, Sandeep Singh Sengar
Metaverse for the Healthcare Industry, 2024
Preface
Enhancing Steganography Through Deep Learning Approaches, 2024
Enhancing Steganography Through Deep Learning Approaches
Sengar, Sandeep Singh, Doss, Srinath, Basheer, Shakila, Chowdhary, Chiranji Lal, Kumar, Vijay
Enhancing Steganography Through Deep Learning Approaches, 2024
The Metaverse Game
C. Vanmathi, Harpreet Kaur Channi, Muhammad Fazal Ijaz, Ritik Srivastava, Sai Meghana Bommana, Lauryn Arora, Chiranji Lal Chowdhary
Metaverse for the Healthcare Industry, 2024
Comparative analysis of GAN-based fusion deep neural models for fake face detection
Musiri Kailasanathan Nallakaruppan, Chiranji Lal Chowdhary, SivaramaKrishnan Somayaji, Himakshi Chaturvedi, Sujatha. R, Hafiz Tayyab Rauf, Mohamed Sharaf
Mathematical Biosciences and Engineering, 2024
A Novel QoS Prediction Model for Web Services Based on an Adaptive Neuro-Fuzzy Inference System Using COOT Optimization
Thandra Jithendra, Mohammad Zubair Khan, S. Sharief Basha, Raja Das, A. Divya, Chiranji Lal Chowdhary, Abdulrahman Alahmadi, Ahmed H. Alahmadi
IEEE Access, 2024
FedEHR: A Federated Learning Approach towards the Prediction of Heart Diseases in IoT-Based Electronic Health Records
Sujit Bebortta, Subhranshu Sekhar Tripathy, Shakila Basheer, Chiranji Lal Chowdhary
Diagnostics, 2023
Investigations in Pattern Recognition and Computer Vision for Industry 4.0
Chowdhary, Chiranji Lal 1975-, Swain, Basanta Kumar, Kumar, Vijay
Investigations in Pattern Recognition and Computer Vision for Industry 4 0, 2023
Preface
Investigations in Pattern Recognition and Computer Vision for Industry 4 0, 2023
Indian sign language to speech conversion using deep learning
Basanta Kumar Swain, Chiranji Lal Chowdhary, Rakesh Gain
Investigations in Pattern Recognition and Computer Vision for Industry 4 0, 2023
Role of quantum computing for healthcare
Harpreet Kaur Channi, Chiranji Lal Chowdhary
Handbook of Research on Quality and Competitiveness in the Healthcare Services Sector, 2023
Blockchain-based IoT e-healthcare
Harpreet Kaur Channi, Chiranji Lal Chowdhary
Handbook of Research on Solving Societal Challenges Through Sustainability Oriented Innovation, 2023
An Experimental Study on the Deviations in Performance of FNNS and CNNS in the Realm of Grayscale Adversarial Images
Mathew D. A. Steve, Shree N. Durga, Lal Chowdhary Chiranji
Journal of Engineering Science and Technology Review, 2023
Digital Twin: Exploring the Intersection of Virtual and Physical Worlds
Devika Menon, Bharath Anand, Chiranji Lal Chowdhary
IEEE Access, 2023
Supply Chain Management Using Blockchain Security Enhancement
Aditi Sharma, Vishal Goar, Manoj Kuri, Chiranji Lal Chowdhary
Lecture Notes in Networks and Systems, 2023
DeepMist: Toward Deep Learning Assisted Mist Computing Framework for Managing Healthcare Big Data
Sujit Bebortta, Subhranshu Sekhar Tripathy, Shakila Basheer, Chiranji Lal Chowdhary
IEEE Access, 2023
Hybridization of Blockchain and Cloud Computing: Overcoming Security Issues in IoT
M. Lawanya Shri, E. Gangadevi, K. Santhi, Chiranji Lal Chowdhary
Hybridization of Blockchain and Cloud Computing Overcoming Security Issues in Iot, 2023
Unlocking the Potential of Digital Twins: A Comprehensive Review of Concepts, Frameworks, and Industrial Applications
Sabrina Manickam, Laasya Yarlagadda, Shynu Padinjappurathu Gopalan, Chiranji Lal Chowdhary
IEEE Access, 2023
SRC: Superior Robustness of COVID-19 Detection from Noisy Cough Data Using GFCC
Basanta Kumar Swain, Mohammad Zubair Khan, Chiranji Lal Chowdhary, Abdullah Alsaeedi
Computer Systems Science and Engineering, 2023
An Astute Automaton Model for Objects Extraction Using Outer Totality Cellular Automata (OTCA)
Sandeep Kumar Sharma, Vijay Shankar Sharma, Shakila Basheer, Amit Chaurasia, Chiranji Lal Chowdhary
IEEE Access, 2023
GEMM, a Genetic Engineering-Based Mutual Model for Resource Allocation of Grid Computing
Sandeep Kumar Sharma, Amit Chaurasia, Vijay Shankar Sharma, Chiranji Lal Chowdhary, Shakila Basheer
IEEE Access, 2023
Non-Gaussian Traffic Modeling for Multicore Architecture Using Wavelet Based Rosenblatt Process
Amit Chaurasia, Vijay Shankar Sharma, Chiranji Lal Chowdhary, Shakila Basheer, Thippa Reddy Gadekallu
IEEE Access, 2023
Key Based Steganography Using Convolutions
Saksham Arora, Pranav Gupta, Vishal Goar, Manoj Kuri, Harpreet Kaur Channi, Chiranji Lal Chowdhary
Lecture Notes in Networks and Systems, 2023
The Laplacian Energy of Hesitancy Fuzzy Graphs in Decision-Making Problems
N. Rajagopal Reddy, Mohammad Zubair Khan, S. Sharief Basha, Abdulrahman Alahmadi, Ahmed H. Alahmadi, Chiranji Lal Chowdhary
Computer Systems Science and Engineering, 2023
Ensemble Model for Diagnostic Classification of Alzheimer’s Disease Based on Brain Anatomical Magnetic Resonance Imaging
Yusera Farooq Khan, Baijnath Kaushik, Chiranji Lal Chowdhary, Gautam Srivastava
Diagnostics, 2022
Multidisciplinary applications of deep learning-based artificial emotional intelligence
Chowdhary, Chiranji Lal 1975-
Multidisciplinary Applications of Deep Learning Based Artificial Emotional Intelligence, 2022
Preface
Multidisciplinary Applications of Deep Learning Based Artificial Emotional Intelligence, 2022
Role of emotional intelligence in agile supply chains
Akshat Mishra, Swetank Kaushik, Srinivasa Perumal R., Chiranji Lal Chowdhary
Multidisciplinary Applications of Deep Learning Based Artificial Emotional Intelligence, 2022
An Efficient and Privacy-Preserving Scheme for Disease Prediction in Modern Healthcare Systems
Shynu Padinjappurathu Gopalan, Chiranji Lal Chowdhary, Celestine Iwendi, Muhammad Awais Farid, Lakshmana Kumar Ramasamy
Sensors, 2022
Breast cancer detection using hybrid computational intelligence techniques
Debi Prasanna Acharjya, Chiranji Lal Chowdhary
Research Anthology on Medical Informatics in Breast and Cervical Cancer, 2022
Hand gesture recognition based on a Harris Hawks optimized Convolution Neural Network
Thippa Reddy Gadekallu, Gautam Srivastava, Madhusanka Liyanage, Iyapparaja M., Chiranji Lal Chowdhary, Srinivas Koppu, Praveen Kumar Reddy Maddikunta
Computers and Electrical Engineering, 2022
Non-invasive Detection of Parkinson’s Disease Using Deep Learning
Chiranji Lal Chowdhary, R. Srivatsan
International Journal of Image Graphics and Signal Processing, 2022
Agile Supply Chain: Framework for Digitization
Chiranji Lal Chowdhary
Studies in Systems Decision and Control, 2022
Deep Learning Empowered Fight Against COVID-19: A Survey
Chiranji Lal Chowdhary, Harpreet Kaur Channi
Studies in Computational Intelligence, 2022
COMPUTER VISION AND RECOGNITION SYSTEMS: Research Innovations and Trends
Chiranji Lal Chowdhary, G. Thippa Reddy, B. D. Parameshachari
Computer Vision and Recognition Systems Research Innovations and Trends, 2022
Digital Transformation in Healthcare Industry: A Survey
Harpreet Kaur Channi, Prateek Shrivastava, Chiranji Lal Chowdhary
Studies in Computational Intelligence, 2022
Preface
Pankaj Chowdhary, Abhay Raj, Digvijay Verma, Yusuf Akhter
Studies in Computational Intelligence, 2022
Data Protection Using Multiple Servers for Medical Supply Chain System
Nikhilesh Saragadam, Suri Koushmitha, Yerru Nanda Krishna Arun, Chiranji Lal Chowdhary
Studies in Systems Decision and Control, 2022
Efficient resource allocation in fog computing using QTCS model
M. Iyapparaja, Naif Khalaf Alshammari, M. Sathish Kumar, S. Siva Rama Krishnan, Chiranji Lal Chowdhary
Computers Materials and Continua, 2022
Past, present and future of gene feature selection for breast cancer classification - a survey
R. Nagendra, S. Swarnalatha
International Journal of Engineering Systems Modelling and Simulation, 2022
Isolated word-based spoken dialogue system using odia phones
Basanta K. Swain, Sanghamitra Mohanty, Chiranji L. Chowdhary
Recent Advances in Computer Science and Communications, 2021
Simple Linear Iterative Clustering (SLIC) and graph theory-based image segmentation
Chiranji Lal Chowdhary
Handbook of Research on Machine Learning Techniques for Pattern Recognition and Information Security, 2021
Performance assessment of supervised classifiers for designing intrusion detection systems: A comprehensive review and recommendations for future research
Ranjit Panigrahi, Samarjeet Borah, Akash Kumar Bhoi, Muhammad Fazal Ijaz, Moumita Pramanik, Rutvij H. Jhaveri, Chiranji Lal Chowdhary
Mathematics, 2021
Spatiotemporal-based sentiment analysis on tweets for risk assessment of event using deep learning approach
M. Parimala, R. M. Swarna Priya, M. Praveen Kumar Reddy, Chiranji Lal Chowdhary, Ravi Kumar Poluru, Suleman Khan
Software Practice and Experience, 2021
Deep learning and medical image processing for coronavirus (COVID-19) pandemic: A survey
Sweta Bhattacharya, Praveen Kumar Reddy Maddikunta, Quoc-Viet Pham, Thippa Reddy Gadekallu, Siva Rama Krishnan S, Chiranji Lal Chowdhary, Mamoun Alazab, Md. Jalil Piran
Sustainable Cities and Society, 2021
Artificial intelligence and machine learning: Recent advances and applications (part ii)
Chiranji Lal Chowdhary
Recent Advances in Computer Science and Communications, 2021
Preface
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches Fundamentals Technologies and Applications, 2021
Vehicle control system based on eye, iris, and gesture recognition with eye tracking
Harpreet Kaur, Chiranji Lal Chowdhary
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches Fundamentals Technologies and Applications, 2021
K-means clustering-based radio neutron star pulsar emission mechanism
Shubham Shrimali, Amritanshu Pandey, Chiranji L. Chowdhary
Recent Advances in Computer Science and Communications, 2021
Lane detection using sliding window for intelligent ground vehicle challenge
Sahil Samantaray, Rushikesh Deotale, Chiranji Lal Chowdhary
Lecture Notes on Data Engineering and Communications Technologies, 2021
An intelligent hybrid system for forecasting stock and forex trading signals using optimized recurrent flann and case-based reasoning
D. K. Bebarta, T. K. Das, C. L. Chowdhary, Xiao-Zhi Gao
International Journal of Computational Intelligence Systems, 2021
Computer vision and recognition-based safe automated systems
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches Fundamentals Technologies and Applications, 2021
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches: Fundamentals, technologies and applications
Chowdhary, Chiranji Lal 1975-, Alazab, Mamoun, Chaudhary, Ankit, Hakak, Saqib, Gadekallu, Thippa Reddy
Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches Fundamentals Technologies and Applications, 2021
An IoT and artificial intelligence-based patient care system focused on COVID-19 pandemic
Vishal Kumar Goar, Nagendra Singh Yadav, Chiranji Lal Chowdhary, Kumaresan P, Mohit Mittal
International Journal of Networking and Virtual Organisations, 2021
FogQSYM: An Industry 4.0 Analytical Model for Fog Applications
M. Iyapparaja, M. Sathish Kumar, S. Siva Rama Krishnan, Chiranji Lal Chowdhary, Byungun Yoon, Saurabh Singh, Gi Hwan Cho
Computers Materials and Continua, 2021
A Framework for Prediction and Storage of Battery Life in IoT Devices using DNN and Blockchain
Siva Rama Krishnan Somayaji, Mamoun Alazab, Manoj MK, Antonio Bucchiarone, Chiranji Lal Chowdhary, Thippa Reddy Gadekallu
2020 IEEE Globecom Workshops GC Wkshps 2020 Proceedings, 2020
Cognitive deep learning: Future direction in intelligent retrieval
Chiranji Lal Chowdhary, Ashraf Darwish, Aboul Ella Hassanien
Research Anthology on Artificial Intelligence Applications in Security, 2020
An efficient segmentation and classification system in medical images using intuitionist possibilistic fuzzy C-mean clustering and fuzzy SVM algorithm
Chiranji Lal Chowdhary, Mohit Mittal, Kumaresan P., P. A. Pattanaik, Zbigniew Marszalek
Sensors Switzerland, 2020
An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture
Swarna Priya R.M., Praveen Kumar Reddy Maddikunta, Parimala M., Srinivas Koppu, Thippa Reddy Gadekallu, Chiranji Lal Chowdhary, Mamoun Alazab
Computer Communications, 2020
A deep neural networks based model for uninterrupted marine environment monitoring
Thippa Reddy G., Swarna Priya R.M., Parimala M., Chiranji Lal Chowdhary, Praveen Kumar Reddy M., Saqib Hakak, Wazir Zada Khan
Computer Communications, 2020
SMO-DNN: Spider monkey optimization and deep neural network hybrid classifier model for intrusion detection
Neelu Khare, Preethi Devan, Chiranji Chowdhary, Sweta Bhattacharya, Geeta Singh, Saurabh Singh, Byungun Yoon
Electronics Switzerland, 2020
Exploring breast cancer classification of histopathology images from computer vision and image processing algorithms to deep learning
International Journal of Advanced Science and Technology, 2020
A Fuzzy based Data Perturbation Technique for Privacy Preserved Data Mining
P. G. Shynu, H Md. Shayan., Chiranji Lal Chowdhary
International Conference on Emerging Trends in Information Technology and Engineering Ic Etite 2020, 2020
An Ensemble based Machine Learning model for Diabetic Retinopathy Classification
G Thippa Reddy, Sweta Bhattacharya, S Siva Ramakrishnan, Chiranji Lal Chowdhary, Saqib Hakak, Rajesh Kaluri, M Praveen Kumar Reddy
International Conference on Emerging Trends in Information Technology and Engineering Ic Etite 2020, 2020
Segmentation and Feature Extraction in Medical Imaging: A Systematic Review
Chiranji Lal Chowdhary, D.P. Acharjya
Procedia Computer Science, 2020
Chest X-ray investigation: A convolutional neural network approach
Tapan K. Das, Chiranji Lal Chowdhary, X.Z. Gao
Journal of Biomimetics Biomaterials and Biomedical Engineering, 2020
Monitoring Quality of Tap Water in Cities Using IoT
Asis Kumar Tripathy, Tapan Kumar Das, Chiranji Lal Chowdhary
Lecture Notes on Multidisciplinary Industrial Engineering, 2020
Analytical study of hybrid techniques for image encryption and decryption
Chiranji Lal Chowdhary, Pushpam Virenbhai Patel, Krupal Jaysukhbhai Kathrotia, Muhammad Attique, Kumaresan Perumal, Muhammad Fazal Ijaz
Sensors Switzerland, 2020
Diabetic retinopathy detection using neural network
Vijay Kumar Gurani, Abhishek Ranjan, Chiranji Lal Chowdhary
International Journal of Innovative Technology and Exploring Engineering, 2019
3D object recognition system based on local shape descriptors and depth data analysis
Chiranji Lal Chowdhary
Recent Patents on Computer Science, 2019
Artificial intelligence and machine learning: Recent advances and applications (part 1)
Chiranji Lal Chowdhary
Recent Patents on Computer Science, 2019
Experimental assessment of beam search algorithm for improvement in image caption generation
C. L. Chowdhary, A. Goyal, Bhavesh Kumar Vasnani
Journal of Applied Science and Engineering, 2019
Breast cancer detection using hybrid computational intelligence techniques
Debi Prasanna Acharjya, Chiranji Lal Chowdhary
Handbook of Research on Emerging Perspectives on Healthcare Information Systems and Informatics, 2018
Segmentation of mammograms using a novel intuitionistic possibilistic fuzzy c-mean clustering algorithm
Chiranji Lal Chowdhary, D. P. Acharjya
Advances in Intelligent Systems and Computing, 2018
An improved tumour identification with Gabor Wavelet segmentation
Chiranji Lal Chowdhary, Tapan Kumar Das, Vijaykumar Gurani, Abhishek Ranjan
Research Journal of Pharmacy and Technology, 2018
Clustering algorithm in possibilistic exponential fuzzy c-mean segmenting medical images
Chiranji Lal Chowdhary, D.P. Acharjya
Journal of Biomimetics Biomaterials and Biomedical Engineering, 2017
Learning work on online educational data with bi-directional mapping
International Journal of Pharmacy and Technology, 2016
Study on level set segmentation based classification using mammograms
International Journal of Pharmacy and Technology, 2016
Survey on grid clustering approach with intuitionistic fuzzy histogram
International Journal of Pharmacy and Technology, 2016
A review on brain lesion image detection using MRI images
International Journal of Pharmacy and Technology, 2016
A review of feature extraction application areas in medical imaging
International Journal of Pharmacy and Technology, 2016
A hybrid scheme for breast cancer detection using intuitionistic fuzzy rough set technique
Chiranji Lal Chowdhary, D. P. Acharjya
Biometrics Concepts Methodologies Tools and Applications, 2016
Breast cancer detection using intuitionistic fuzzy histogram hyperbolization and possibilitic fuzzy c-mean clustering algorithms with texture feature based classification on mammography images
Chiranji Lal Chowdhary, D. P. Acharjya
ACM International Conference Proceeding Series, 2016
A hybrid scheme for breast cancer detection using intuitionistic fuzzy rough set technique
Chiranji Lal Chowdhary, D. P. Acharjya
International Journal of Healthcare Information Systems and Informatics, 2016
Decrease in false assumption for detection using digital mammography
Chiranji Lal Chowdhary, Gudavalli Vijaya Krishna Sai, D. P. Acharjya
Advances in Intelligent Systems and Computing, 2016
Three-dimensional object recognition based intelligence system for identification
Chiranji Lal Chowdhary, Kanguana Muatjitjeja, Dharm Singh Jat
Proceedings of 2015 International Conference on Emerging Trends in Networks and Computer Communications Etncc 2015, 2015
Monitoring application for DoS attacks using group-testing
Vijay Kumar Gurani, P. G. Shynu, Chiranji Lal Chowdhary
2014 International Conference on Electronics and Communication Systems Icecs 2014, 2014
Image registration with new system for ensemble of images of multi-sensor registration
World Applied Sciences Journal, 2013
Classification of ECG beats using features from two-stage two-band wavelet decomposition
Journal of Theoretical and Applied Information Technology, 2013
Design and implementation of secure, platform-free, and network-based remote controlling and monitoring system
Chiranji Lal Chowdhary, P. V. S. S. R. Chandra Mouli
International Conference on Pattern Recognition Informatics and Medical Engineering Prime 2012, 2012

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