Dattaprasad A. Torse

Scopus Publications

EEG Spectral Analysis of Mindfulness Based on EEMD and GNNs
Siddharth S. Pedanekar, Dattaprasad Torse
Proceedings of the 4th International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2026, 2026
The paper presents a hybrid EEMD-GNN system to study the EEG patterns that are happening in the process of mindfulness and non-mindfulness meditation. The EEMD technique breaks down EEG signals into intrinsic mode functions (IMFs) to adaptively extract theta and beta band information in a noise-resilient manner, and the GNNs to learn the spatial-temporal connectivity of EEG channels based on phase-locking value and coherence. Tests on both public data sets indicate that the suggested model is highly accurate, with 94% accuracy, which is better than the traditional spectral techniques and performs well in tracking beta and theta variation in frontal and parietal regions. Signal decomposition/graph-based learning can be an effective method to understand the reader in neural dynamics during meditation.
Fuzzy Attention SegNet Model with Serval Ablation Optimization and Log-Cosh Softmax Loss for Effective Brain Tumor Segmentation Using MRI Imaging
C. K. Jyothi, Anupama S. Awati, Dattaprasad A. Torse
Biomedical Materials and Devices, 2026
Scour prediction downstream of an ogee weir using group method of data handling neural network
Rajkumar V. Raikar, Rajashri Khanai, Dattaprasad A. Torse, Tejas D. Doshi, Manisha Tapale
Neural Computing and Applications, 2025
A Novel Light Weight Neural Network using Depth-Wise Separable Convolutions for Plant Disease Classification
Rithambara Rajput, Suneeta Budihal, Saroja Siddamal, Dattaprasad Torse
Aip Conference Proceedings, 2025
EEG-Based Stress Detection: EEMD-Enhanced Features with SVM and Twin-SVM Models
Anusha Kudachi, Dattaprasad A. Torse
2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation Iatmsi 2025, 2025
Recent advances in signal processing and machine learning have significantly advanced EEG-based applications, especially in emotion detection and cognitive analysis. Using Intrinsic Mode Functions (IMFs) developed from Ensemble Empirical Mode Decomposition (EEMD) for improved feature extraction, this work investigates an EEG-based emotional stress identification system. The EEG signals were collected in EDF format, pre-processed by segmenting them into 10-second chunks, ensuring consistent and manageable data windows across all channels. IMFs were extracted from these segments to capture complex frequency components, which were then used as input features for machine learning classifiers. Support Vector Machine (SVM) and Twin Support Vector Machine (Twin SVM) classifiers were used to assess the system. The SVM classifier achieved an accuracy of 80.75%, while the Twin SVM classifier demonstrated a higher training accuracy of 89. 75% and Twin SVM shows an improvement in test accuracy of 93.75%. These results suggest that, while SVM offers good training performance, Twin SVM provides more reliable generalization to unseen data. The findings offer valuable insight into effective pre-processing techniques and the potential of these classifiers for real-time stress detection systems.
EEG-Based Early Diagnosis of Alzheimer's Disease via Tunable Q-factor Wavelet Transform and Deep Stacked BiLSTM Model
Sudhiksha Hanji, Dattaprasad A. Torse, Giridhar Hebbale, Salma Shahapur
5th IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2025, 2025
Alzheimer’s Disease (AD) still represents a significant health issue, and the early and accurate diagnosis has been a clinical need problem. Electroencephalography (EEG) is also now an attractive non-invasive modality to measure finegrained neural change related to early AD but due to its nonstationary nature and vulnerability to noise, demanding more complex methods of analysis. Over the last ten years, much has been accomplished in the form of applying one of the joint timefrequency techniques, the tunable Q Wavelet Transform (TQWT), and combining deep learning models like Bidirectional Long Short-Term Memory (BiLSTM) in order to have a cumulative effect of both improving the interpretability and accuracy of EEG-based diagnostics. The paper has identified issues such as clinical variability, accuracy, and rigorous evaluation frameworks as challenges that still persist in the field. The paper demonstrates 94% accuracy on EEG signals recorded under the condition of eyes closed and resting state through a BiLSTM network that can effectively capture forward and backward temporal dependence of the EEG signal to capture the temporal features and adaptive multi-resolution decomposition to view clearly the non-stationary EEG components of the EEG signal with TQWT Q = 4 and r = 3. In general, these findings summarize existing developments and outline the existing gaps to inform future studies on how EEG-based solutions can be developed to be clinically viable in order to diagnose early onset AD.
EEG-Based Driver Drowsiness Detection: A Data-driven Approach for Enhancing Road Safety
Preeti Paschapuri, Diksha Nalawade, Rahul Kundargi, Basavaraj Mujagoni, Dattaprasad A. Torse
International Conference on Communication Computer and Information Technology Ic3it 2025, 2025
Development of Music Recommendation System Using Machine Learning Techniques
Anjali Madhale, Rahul Kudachi, Rahul Basapur, Ranjita Nayanegali, D A Torse
2025 Global Conference on Information Technology and Communication Networks Gitcon 2025, 2025
Music is one of the most popular forms of entertainment in the digital age, offering a huge collection of songs in different styles such as pop, rock, jazz, blues, and folk. Music recommendation systems have been developed to assist users to find something through vast libraries of songs into the desired content. In this paper, we outlined a music recommendation system tailored to individual preferences utilizing the K-nearest Neighbor (KNN) algorithm. The system uses a decision tree to classify user preferences and predict song recommendations based on features extracted from the Spotify dataset, including genre, tempo, energy, and acousticness. The proposed model uses decision tree, Random Forest, and KNN regression algorithm to predict songs that have mode similarity between songs, audio features of songs, and songs are predicted using KNN Regression algorithm. We found that the KNN model would be the best in terms of accuracy for genre prediction. The production of this recommendation system allows for major developments in the future, including better personalization through real-time updates, hybrid models, and most importantly the incorporation of some aspects of social media trends. This paper explores the integration of machine learning techniques into music recommendation systems, highlighting contributions towords personalized music discovery and areas where further advancement is needed to optimize user satisfaction and platform profitability.
A Machine Learning Approach to English-Togerman Translation using MarianMT
Kalashri Gomannache, Pruthviraj Nesarikar, Diya Revankar, Radhesh Patil, Dattaprasad A. Torse
Proceedings of IEEE International Conference for Women in Innovation Technology and Entrepreneurship Icwite 2025, 2025
Machine Translation (MT) is used for transforming one language into another while keeping the meaning of the input text and creating accurate and fluent text in the output language. This paper presents a language translation model that translates from English to German. The model provides a user-friendly interface that allows users to provide input in the form of text and speech. The proposed model of text and voice translation is examined on large datasets such as the Google machine translation kit and Google speech recognition. This model uses Marian MT, which uses a Recurrent Neural Network (RNN) for text-to-text conversion and audio-to-text conversion. The paper also describes various aspects such as data preprocessing, model architecture design, training processes, and analysis through comparative studies. The results prove that the system works well with a Word Error Rate(WER) of 20%, which indicates that recognition errors are low. A BLEU score of 140 is obtained, which means the quality of translations is high. In all, the overall error rate stood at 5% to prove the system works accurately. For latency, there was recognition at 20 ms, translation at 10 ms, and synthesis took 15 ms, the total delay being 45 ms, which makes the system fast enough for real-time use. Our model describes how useful the model could be, for example, learning a new language, a communication aid for the speech and hearing impaired, or cross-border business. The proposed model intends to bridge the language gap and facilitate communication among people from different linguistic backgrounds.
Context-Aware Product Recommendation System
Nandeesh Katkol, Priyanshu Porwal, Priyanka Budihal, Jamuna Pulpatli, Dattaprasad A. Torse
2025 IEEE 4th International Conference for Advancement in Technology Iconat 2025, 2025
Recommender systems are the tools that help the user by suggesting the items or products according to his previous preferences. Such systems are used extensively in e-commerce websites, entertainment, education, and media. Traditional recommendation systems treat the task as a sequential prediction problem. However, newer methods like Markov Decision Processes (MDPs) take into account the long-term impact of recommendations. These methods connect the products with the customer's ID, hence work more efficiently. For practical use, these systems must work fast and require less memory. Other approaches combine machine learning algorithms for finding patterns between products and grouping customers based on their profiles such as k-means clustering or SVM. These hybrid models can connect customer behaviour with specific product associations. For instance, a hygiene retailer study demonstrated how machine learning can identify product links and unique customer traits. With so many options available today, recommender systems help user to find what they need by filtering data and suggesting the most relevant products. While each method has its pros and cons, improving these systems requires studying their performance. Our model achieves an Precision of 86.7 % and Recall of 83.2% resulting in an F1 score of 84.9%.
Structural crack detection, segmentation, and classification: A review
Basavaraj Katageri, Rajashri Khanai, Rajkumar V Raikar, Dattaprasad A Torse, Krishna Pai
Data Analytics for Intelligent Systems Techniques and Solutions, 2024
Design and implementation of low-power, high-speed, reliable and secured Hardware Accelerator using 28 nm technology for biomedical devices
Swati Mavinkattimath, Rajashri Khanai, Dattaprasad Torse, Nalini Iyer
Biomedical Signal Processing and Control, 2024
Optimizing Brain Tumor Segmentation in MRI images with Enhanced nnU-Net
C K Jyothi, Anupama Awati, Dattaprasad Torse
2nd IEEE International Conference on Networks Multimedia and Information Technology Nmitcon 2024, 2024
Building Surface Crack Detections Using Deep Convolutional Neural Network (DCNN) Architectures
Rajashri Khanai, Basavaraj Katageri, Dattaprasad Torse, Rajkumar Raikar
Lecture Notes in Civil Engineering, 2024
Soil Moisture Detection Using Arduino Sensor and ANN Prediction
Rajkumar Raikar, Basavaraj Katageri, Rajashri Khanai, Dattaprasad Torse, Praveen Mannikatti
Lecture Notes in Civil Engineering, 2024
Survey on IoT-enabled 6G wireless systems
Sanjeev Sharma, Dharmendra Dixit
6g Communication Network Architecture Security and Applications, 2024
Optimal feature selection for COVID-19 detection with CT images enabled by metaheuristic optimization and artificial intelligence
Dattaprasad A. Torse, Rajashri Khanai, Krishna Pai, Sridhar Iyer, Swati Mavinkattimath, Rakhee Kallimani, Salma Shahpur
Multimedia Tools and Applications, 2023
Neural Crypto-Coding Based Approach to Enhance the Security of Images over the Untrusted Cloud Environment
Pallavi Kulkarni, Rajashri Khanai, Dattaprasad Torse, Nalini Iyer, Gururaj Bindagi
Cryptography, 2023
FSRCLP: Fuzzy Based Secure Reliable Cross Layer Protocol for Underwater Acoustic Communication
Salma S. Shahapur, Rajashri Khanai, D. A. Torse
Wireless Personal Communications, 2023
The Impact of Implementation and Evaluation of Engineering Exploration Activities in a First-Year Engineering Course
, Basavaraj G. Katageri, Dattaprasad A. Torse, , Rajashri Khanai, , Krishna Pai, and
Journal of Engineering Education Transformations, 2023
A Survey on Semantic Communications for Intelligent Wireless Networks
Sridhar Iyer, Rajashri Khanai, Dattaprasad Torse, Rahul Jashvantbhai Pandya, Khaled M. Rabie, Krishna Pai, Wali Ullah Khan, Zubair Fadlullah
Wireless Personal Communications, 2023
SURFACE CRACK DETECTION USING DEEP LEARNING FRAMEWORK FOR CIVIL STRUCTURES
Structural Integrity and Life, 2023
Semantic Communications enabled Intelligent Wireless Networks
Sridhar Iyer, Rahul Pandya, Rajashri Khanai, Dattaprasad Torse, Krishna Pai, Rakhee Kallimani
Proceedings of the 10th International Conference on Signal Processing and Integrated Networks Spin 2023, 2023
Performance Analysis of Error Control Codes for Underwater Wireless Acoustic Communication
Salma S. Shahapur, Rajashri Khanai, Dattaprasad A. Torse
Trends in Sciences, 2022
Simulation of OFDM MIMO with IDMA for Underwater Acoustic Communication
Salma S. Shahapur, Rajashri Khanai, D. A. Torse
Lecture Notes in Electrical Engineering, 2022
Hardware Implementation of Automated Seizure Detection System using EEG Signals and Edge Computing
Dattaprasad A. Torse, Rajashri Khanai, Krishna Pai, Sridhar Iyer
2022 6th International Conference on Trends in Electronics and Informatics Icoei 2022 Proceedings, 2022
Comparative Analysis of OFDM MIMO and IDMA OFDM MIMO using Aqua Sim Simulator for Underwater Communication
Salma S Shahapur, Dr Rajshri Khanai, Dr D A Torse
Journal of Physics Conference Series, 2021
Classification of Epileptic Seizures using Ensemble Empirical Mode Decomposition and Least Squares Support Vector Machine
Dattaprasad A. Torse, Rajashri Khanai
2021 International Conference on Computer Communication and Informatics Iccci 2021, 2021
An optimized design of seizure detection system using joint feature extraction of multichannel EEG signals
Dattaprasad Torse, Veena Desai, Rajashri Khanai
Journal of Biomedical Research, 2020
Detection of leaf disease using hybrid feature extraction techniques and CNN classifier
Vidyashree Kanabur, Sunil S. Harakannanavar, Veena I. Purnikmath, Pramod Hullole, Dattaprasad Torse
Advances in Intelligent Systems and Computing, 2020
An Extensive Review of Feature Extraction Techniques, Challenges and Trends in Automatic Speech Recognition
, Vidyashree Kanabur, Sunil S Harakannanavar, Dattaprasad Torse
International Journal of Image Graphics and Signal Processing, 2019
Classification of epileptic seizures using recurrence plots and machine learning techniques
Dattaprasad A. Torse, Rajashri Khanai, Veena V. Desai
Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing Iccsp 2019, 2019
A survey on secured wireless body sensor networks
Swati G. Mavinkattimath, Rajashri Khanai, Dattaprasad A. Torse
Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing Iccsp 2019, 2019
Comprehensive Study of Data Aggregation Models, Challenges and Security Issues in Wireless Sensor Networks
Department of Electronics, Communication Engineering, S G Balekundri Institute of Technology, Belagavi, India, Veena I Puranikmath, Sunil S Harakannanavar, Satyendra Kumar, Dattaprasad Torse
International Journal of Computer Network and Information Security, 2019
Classification of eeg signals in seizure detection system using ellipse area features and support vector machine
Dattaprasad A. Torse, Veena Desai, Rajashri Khanai
Advances in Intelligent Systems and Computing, 2019
FPGA implementation of a Micro controller Unit for Body Sensor Network
Swati G. Mavinkattimath, Rajashri Khanai, Dattaprasad A. Torse
Proceedings of the International Conference on Computational Techniques Electronics and Mechanical Systems Ctems 2018, 2018
Epilepsy Detection by Processing of EEG signals using LabVIEW Simulation
S. N. Hallur, D. A. Torse, V.K. Aithal, S.S. Santaji
3rd International Conference on Electrical Electronics Communication Computer Technologies and Optimization Techniques Iceeccot 2018, 2018
Multi-channel EEG Analysis Using Discrete Wavelet Transform and Machine Learning Classifiers
Dattaprasad A. Torse, Veena V. Desai, Rajashri Khanai
Proceedings of the 2018 IEEE International Conference on Communication and Signal Processing Iccsp 2018, 2018
Design of adaptive EEG preprocessing algorithm for neurofeedback system
Dattaprasad A. Torse, Veena V. Desai
International Conference on Communication and Signal Processing Iccsp 2016, 2016
Neural crypto-coding as DES: Turbo over land mobile satellite (LMS) channel
Rajashri Khanai, G. H. Kulkarni, Dattaprasad A. Torse
International Conference on Communication and Signal Processing Iccsp 2014 Proceedings, 2014
AES-TURBO as a single primitive for land mobile satellite channel
Rajashri Khanai, G. H. Kulkarni, Dattaprasad A. Torse
2014 IEEE Students Conference on Electrical Electronics and Computer Science Sceecs 2014, 2014
Crypto-coding technique for land mobile satellite channel
Rajashri Khanai, G.H. Kulkarni, Dattaprasad A. Torse
Proceedings 2014 5th International Conference on Signal and Image Processing Icsip 2014, 2014

RECENT SCHOLAR PUBLICATIONS

EEG Spectral Analysis of Mindfulness Based on EEMD and GNNs
SS Pedanekar, D Torse
2026 4th International Conference on Intelligent Data Communication … , 2026
2026
Fuzzy Attention SegNet Model with Serval Ablation Optimization and Log-Cosh Softmax Loss for Effective Brain Tumor Segmentation Using MRI Imaging
CK Jyothi, AS Awati, DA Torse
Biomedical Materials & Devices, 1-25 , 2026
2026
EEG-Based Early Diagnosis of Alzheimer’s Disease via Tunable Q-factor Wavelet Transform and Deep Stacked BiLSTM Model
S Hanji, DA Torse, G Hebbale, S Shahapur
2025 5th International Conference on Mobile Networks and Wireless … , 2025
2025
EEG-Based Driver Drowsiness Detection: A Data-driven Approach for Enhancing Road Safety
P Paschapuri, D Nalawade, R Kundargi, B Mujagoni, DA Torse
2025 International Conference on Communication, Computer, and Information … , 2025
2025
A Machine Learning Approach to English-Togerman Translation using MarianMT
K Gomannache, P Nesarikar, D Revankar, R Patil, DA Torse
2025 IEEE International Conference for Women in Innovation, Technology … , 2025
2025
Context-Aware Product Recommendation System
N Katkol, P Porwal, P Budihal, J Pulpatli, DA Torse
2025 IEEE 4th International Conference for Advancement in Technology (ICONAT … , 2025
2025
Development of Music Recommendation System Using Machine Learning Techniques
A Madhale, R Kudachi, R Basapur, R Nayanegali, DA Torse
2025 Global Conference on Information Technology and Communication Networks … , 2025
2025
EEG-Based Stress Detection: EEMD-Enhanced Features with SVM and Twin-SVM Models
A Kudachi, DA Torse
2025 IEEE International Conference on Interdisciplinary Approaches in … , 2025
2025
Citations: 1
Scour prediction downstream of an ogee weir using group method of data handling neural network
RV Raikar, R Khanai, DA Torse, TD Doshi, M Tapale
Neural Computing and Applications 37 (5), 3793-3807 , 2025
2025
Citations: 1
A novel light weight neural network using depth-wise separable convolutions for plant disease classification
R Rajput, S Budihal, S Siddamal, D Torse
AIP Conference Proceedings 3253 (1), 030035 , 2025
2025
Citations: 1
Survey on IoT-enabled 6G wireless systems
S Iyer, RJ Pandya, R Kallimani, K Pai, R Khanai, DA Torse, ...
6G Communication Network, 117-134 , 2024
2024
Optimizing Brain Tumor Segmentation in MRI images with Enhanced nnU-Net
CK Jyothi, A Awati, D Torse
2024 Second International Conference on Networks, Multimedia and Information … , 2024
2024
Citations: 3
Structural crack detection, segmentation, and classification: a review
B Katageri, R Khanai, RV Raikar, DA Torse, K Pai
Data Analytics for Intelligent Systems: Techniques and solutions, 13-1-13-16 , 2024
2024
Citations: 2
Design and implementation of low-power, high-speed, reliable and secured Hardware Accelerator using 28 nm technology for biomedical devices
S Mavinkattimath, R Khanai, D Torse, N Iyer
Biomedical Signal Processing and Control 88, 105554 , 2024
2024
Citations: 5
Secure Fuzzy Simple Shortest Path Routing Protocol (SF_SSP) for Underwater Communication
SS Shahapur, R Khanai, DA Torse, CA Nerurkar, HP Rajani
Indian Journal of Science and Technology 16 (44), 4016-4025 , 2023
2023
Citations: 1
Optimal feature selection for COVID-19 detection with CT images enabled by metaheuristic optimization and artificial intelligence
DA Torse, R Khanai, K Pai, S Iyer, S Mavinkattimath, R Kallimani, ...
Multimedia Tools and Applications 82 (26), 41073-41103 , 2023
2023
Citations: 15
HS-HA: Design of High-Speed Hardware Accelerator SOC for Biomedical Applications
S Mavinkattimath, R Khanai, D Torse, N Iyer
2023
Soil Moisture Detection Using Arduino Sensor and ANN Prediction
R Raikar, B Katageri, R Khanai, D Torse, P Mannikatti
International Conference on Interdisciplinary Approaches in Civil … , 2023
2023
Citations: 2
Building Surface Crack detections using deep convolutional neural network (DCNN) architectures
R Khanai, B Katageri, D Torse, R Raikar
International Conference on Interdisciplinary Approaches in Civil … , 2023
2023
Citations: 1
Neural crypto-coding based approach to enhance the security of images over the untrusted cloud environment
P Kulkarni, R Khanai, D Torse, N Iyer, G Bindagi
Cryptography 7 (2), 23 , 2023
2023
Citations: 5

MOST CITED SCHOLAR PUBLICATIONS

A survey on semantic communications for intelligent wireless networks
S Iyer, R Khanai, D Torse, RJ Pandya, KM Rabie, K Pai, WU Khan, ...
Wireless Personal Communications 129 (1), 569-611 , 2023
2023
Citations: 94
Classification of epileptic seizures using recurrence plots and machine learning techniques
DA Torse, R Khanai, VV Desai
2019 International Conference on Communication and Signal Processing (ICCSP … , 2019
2019
Citations: 33
A review on seizure detection systems with emphasis on multi-domain feature extraction and classification using machine learning
V Desai, A EduSoft
BRAIN–Broad Research in Artificial Intelligence and Neuroscience , 2017
2017
Citations: 28
A survey on secured wireless body sensor networks
SG Mavinkattimath, R Khanai, DA Torse
2019 International Conference on Communication and Signal Processing (ICCSP … , 2019
2019
Citations: 26
Detection of leaf disease using hybrid feature extraction techniques and CNN classifier
V Kanabur, SS Harakannanavar, VI Purnikmath, P Hullole, D Torse
International Conference On Computational Vision and Bio Inspired Computing … , 2019
2019
Citations: 25
An extensive review of feature extraction techniques, challenges and trends in automatic speech recognition
V Kanabur, SS Harakannanavar, D Torse
International Journal of Image, Graphics and Signal Processing 11 (5), 1-12 , 2019
2019
Citations: 17
Optimal feature selection for COVID-19 detection with CT images enabled by metaheuristic optimization and artificial intelligence
DA Torse, R Khanai, K Pai, S Iyer, S Mavinkattimath, R Kallimani, ...
Multimedia Tools and Applications 82 (26), 41073-41103 , 2023
2023
Citations: 15
Design of adaptive EEG preprocessing algorithm for neurofeedback system
DA Torse, VV Desai
2016 international conference on communication and signal processing (iccsp … , 2016
2016
Citations: 15
Comprehensive study of data aggregation models, challenges and security issues in wireless sensor networks
VI Puranikmath, SS Harakannanavar, S Kumar, D Torse
International Journal of Computer Network and Information Security 11 (3), 30 , 2019
2019
Citations: 14
Survey on Internet of Things enabled by 6G wireless networks
S Iyer, RJ Pandya, R Kallimani, K Pai, R Khanai, D Torse, ...
arXiv preprint arXiv:2203.08426 , 2022
2022
Citations: 12
Nonlinear blind source separation for EEG signal pre-processing in brain-computer interface system for epilepsy
DA Torse, RR Maggavi, SA Pujari
International Journal of Computer Applications 50 (14), 12-19 , 2012
2012
Citations: 12
An optimized design of seizure detection system using joint feature extraction of multichannel EEG signals
D Torse, V Desai, R Khanai
Journal of biomedical research 34 (3), 191 , 2020
2020
Citations: 11
Classification of EEG signals in a seizure detection system using dual tree complex wavelet transform and least squares support vector machine
D Torse, V Desai, R Khanai
International Journal of Image, Graphics and Signal Processing 10 (1), 56-64 , 2018
2018
Citations: 10
Performance analysis of underwater acoustic communication using IDMA-OFDM-MIMO with Reed Solomon and turbo code
R Khanai, SS Shahapur, D Torse
International Journal of Computer Network and Information Security 10 (12 … , 2018
2018
Citations: 10
Performance analysis of conventional crypto-coding
R Khanai, GH Kulkarni, DA Torse
International Journal of Latest Trends in Computing 193, 193-197 , 2011
2011
Citations: 9
Fsrclp: Fuzzy based secure reliable cross layer protocol for underwater acoustic communication
SS Shahapur, R Khanai, DA Torse
Wireless Personal Communications 129 (4), 2813-2828 , 2023
2023
Citations: 7
Hardware implementation of automated seizure detection system using EEG signals and edge computing
DA Torse, R Khanai, K Pai, S Iyer
2022 6th International Conference on Trends in Electronics and Informatics … , 2022
2022
Citations: 7
Classification of epileptic seizures using ensemble empirical mode decomposition and least squares support vector machine
DA Torse, R Khanai
2021 International Conference on Computer Communication and Informatics … , 2021
2021
Citations: 7
A cloud based medical transcription using speech recognition technologies
S Kulkarni, DA Torse, D Kulkarni
International Research Journal of Engineering and Technology 7 (5), 6160-6163 , 2020
2020
Citations: 7
FPGA implementation of a Micro controller Unit for Body Sensor Network
SG Mavinkattimath, R Khanai, DA Torse
2018 International Conference on Computational Techniques, Electronics and … , 2018
2018
Citations: 7

Dattaprasad A. Torse

RESEARCH, TEACHING, or OTHER INTERESTS

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

MOST CITED SCHOLAR PUBLICATIONS