PURUSHOTHAMAN KESAVALU ELUMALAI

@veltech.edu.in

Assistant Professor and Electronics & Communication Engineering
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

PURUSHOTHAMAN KESAVALU ELUMALAI


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https://researchid.co/purushothamankesavaluelumalai
has made remarkable achievement in the areas of teaching,
research, invention and extension activities. He had experience in dissertations and a
research project in 5G wireless communication has 9 papers to his credit in reputed journals
and various conference Proceedings.
is a celebrated member of Professional bodies such as
Professional member of Institute of Electrical and Electronics Engineers in USA, Life
Associate member of International Association of Engineers (IAENG), Inc. Hong Kong,
Professional Member in Institute for Engineering Research and Publication (IFERP), India,
Senior Member in Institute of Research Engineers and Doctors (IRED), USA.
He is a Technical Chair of AICTE sponsored IEEE International Conference on
Communication and Signal processing (ICCSP‟16) and IEEE International Conference on
Communication and signal processing (ICCSP‟17, 18, 19, 20).

EDUCATION

Ph.D., - Anna University, Year of Passing 2021
M.E., - Anna University, Year of Passing 2016
B.E., - Anna University, Year of Passing 2014

RESEARCH INTERESTS

Wireless Communication, Wireless sensor Networks, VLSI
design
29

Scopus Publications

190

Scholar Citations

8

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • HRL-GT: A Hybrid Reinforcement Learning and Game Theory Framework for Energy-Efficient Cluster Head Election and Routing in Underwater Sensor Networks
    Sivsakthiselvan S, Palanivelan M, Sridevi N, Purushothaman K E
    2025 2nd International Conference on Computing and Data Science Iccds 2025, 2025
    Underwater Wireless Sensor Networks (UWSNs) are critical for various marine applications, including environmental monitoring, disaster prediction, and military surveillance. However, these networks face persistent challenges such as energy constraints, dynamic topology, and high propagation delays. To address these limitations, this paper proposes a novel Hybrid Reinforcement Learning with Game Theory (HRL-GT) framework for cluster head (CH) election and adaptive routing in UWSNs. The proposed model integrates a Deep Q-Network (DQN)-based learning agent for optimizing routing decisions with a game-theoretic approach for fair and energy-efficient CH selection. By jointly considering factors such as residual energy, node depth, and link quality, HRL-GT ensures both stability and adaptability in routing and clustering mechanisms. Performance evaluation through MATLAB simulations demonstrates that HRL-GT significantly improves network lifetime, reduces energy consumption, enhances packet delivery ratio (PDR), and minimizes CH change rates when compared to existing protocols such as EA-DBSEP-IoUT, DBSEP, and EEACA. The results validate the effectiveness of HRL-GT in extending the operational longevity and reliability of UWSNs in harsh underwater environments.
  • EA-DBSEP-IoUT: An Edge-Assisted Depth-Based Stable Election Protocol for Energy-Efficient Routing in IoUT
    Sivsakthiselvan S, Pavithra S, Purushothaman K E, P Radhakrishnan, Samsudeen S
    Proceedings of the 2025 11th International Conference on Communication and Signal Processing Iccsp 2025, 2025
    The Internet of Underwater Things (IoUT) is a rapidly evolving field with applications in environmental monitoring, disaster prevention, and military surveillance. However, underwater sensor networks face unique challenges, including high propagation delay, energy constraints, and dynamic topology changes. Traditional routing protocols such as the Stable Election Protocol for IoUT (SEP-IoUT) and Depth-Based Routing (DBR) suffer from inefficient cluster head (CH) selection, leading to rapid energy depletion. This paper proposes Edge-Assisted Depth-Based Stable Election Protocol for IoUT (EA-DBSEP-IoUT), an energy-efficient, edge-assisted adaptive clustering scheme. The proposed method integrates Reinforcement Learning (RL) for optimal CH selection, data aggregation at edge nodes, and multi-hop routing to reduce communication overhead. Simulation results demonstrate that EA-DBSEP-IoUT outperforms SEP-IoUT, Depth-Based Unequal Clustering (DBUC), and Energy-Efficient Depth-Based Routing (EEDBR) in terms of network lifetime, energy efficiency, and stability period.
  • Precision Driven Sentiment and Topic Classification of News Articles using IndicBert Model (IBM)
    Banu Priya Prathaban, R Subash, Ben Sujin, K.E. Purushothaman, G Lakshmi
    2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
    This paper explores the application of machine learning models for sentiment analysis and topic classification of news articles. We employed multiple models including VGGNet, Alexnet and advanced transformer-based models like IndicBERT model (IBM) to classify news articles based on their sentiment and topics. The study utilized a dataset of news headlines from Indian Express, leveraging TF-IDF vectorization and BERT embeddings for feature extraction. Our results show that VGGNet on IndicBERT (IBM) embeddings outperforms traditional methods in terms of accuracy, precision, and recall. We also demonstrate the effectiveness of these models through confusion matrices and performance metrics, highlighting the potential for improving news classification systems. The VGGNet model achieved strong performance with an accuracy of 87.5%, precision of 65%, recall of 70%, and an $F 1$ score of 68%, showing good balance in sentiment classification. Similarly, the Alexnet model performed comparably with an accuracy of 87.1%, precision of 61%, recall of 68%, and an F1 score of 65%.
  • Enhanced Variational Quantum Networks for EarlyAlzheimer's Detection: A Quantum-Classical Approach
    S. Samsudeen, M. Salomi Samsudeen, K.E. Purushothaman, P. Radhakrishnan, S. Sivasakthiselvan
    Proceedings of the 2025 11th International Conference on Communication and Signal Processing Iccsp 2025, 2025
    The population aged 60 years is rapid increased to 20% of the total Indian population according to the statistics. Alzheimer is a disease which is a neurogenerative disorder. It is considered as the major cause of dementia. India is in critical scenario that faces increase in the elder population suffering from dementia. Hence, there arise a need for early diagnosis of Alzheimer disease (AD) in order to improve the patient’s mental health condition. Though, the existing diagnostic methods are accurate and fast computing, there arise a need to propose a model that aids in improved accuracy and reducing the computational time for early prediction of AD.The proposed model uses Enhanced variational Quantum Network(VAQ) that aids in improving the potential of AD in terms of accuracy and time complexity is designed to decide the feature extraction by processing the huge voluminous images and then fed the outcome into the classifier model. Alzheimer disease neuroimaging stage I and stage II are the datasets considered for applying VAQ for AD prediction. Both stage I and stage II dataset were combined together in order to process the resource efficiently for the diagnosis performs feature extraction and then the results been fed as input to the Quantum classifier. The classifier processes the data and classify the images as no dement, mild dement, average dement, very mild dement. The results are compared with already existing Convolutional Neural Network model (CNN) and Ensemble Classifier.
  • Analysis and Prediction of Road Accidents using Vision Transformer Model (VTM)
    Banu Priya Prathaban, D Saveetha, M. Sangeetha, Ashwini, K.E. Purushothaman, Ganeshkumar N
    2025 8th International Conference on Circuit Power and Computing Technologies Iccpct 2025, 2025
    Road safety is a significant global concern, as accidents result in substantial fatalities, injuries, and economic costs. This work aims to build an intelligent system using a vast historical dataset of accidents assessing and forecasting road accidents. The system develops a Vision Transformer Model (VTM) using Apache Spark’s distributed computing capability for data preprocessing and TensorFlow’s sophisticated machine learning capability. To forecast accident severity, the model combines many elements including weather conditions, road characteristics, temporal patterns, and location data. The study underlines the need of knowing accident-prone areas and underlying causes to improve road safety and eventually lower the frequency of the next accidents. The dataset we have used is a sample one month dataset from the referred public dataset on accident. We have implemented multiple deep learning classification models to predict the severity of the accidents including CNN models specifically CoAtNet, ConvNeXt and RegNet. Also, we have compared performance metrics with other classification models. Our study has resulted in testing accuracy of around 0.9567 and training accuracy of around 0.9834.
  • Advancing Early Oral Cancer Detection with Image Processing and AI
    K. E. Purushothaman, A. N. Arularasan, Addanki Purna Ramesh, S. Selvi, Yousef Farhaoui, S. Gopalakrishnan
    Lecture Notes in Networks and Systems, 2025
  • Enhancing cybersecurity in cloud computing and WSNs: A hybrid IDS approach
    K. Sundaramoorthy, K.E. Purushothaman, J. Jeba Sonia, N. Kanthimathi
    Computers and Security, 2024
  • Improved Energy-Saving Multi-hop Networking in Wireless Networks
    D. David Neels Ponkumar, S. Ramesh, K. E. Purushothaman, M. R. Arun
    Lecture Notes in Networks and Systems, 2024
  • Brain Tumor Classification Using CNNs
    D Saveetha, Banu Priya Prathaban, A Rashmi, K. E. Purushothaman
    4th International Conference on Power Energy Control and Transmission Systems Harnessing Power and Energy for an Affordable Electrification of India Icpects 2024, 2024
    Brain tumors are abnormal cell growths in the brain that can have a major negative impact on one's health. For efficient treatment planning, brain tumor classification must be precise. Convolutional Neural Networks (CNNs) have been an effective technique for the automated classification of brain tumors in recent years. Convolutional Neural Network (CNN) is the most popular neural network model for the image classification problem, which has attracted a lot of interest in recent years. In this paper, we suggest a CNN model for classifying brain tumors that performs quite well on a publicly accessible dataset. We contrast our model's performance with that of earlier research and talk about how our findings might have medical applications. Our findings demonstrate the need for more research in this field and show how well CNNs can classify brain tumors. The proposed CNN-based approach aims to accurately classify three major types of brain tumors, namely glioma, meningioma, and pituitary tumor. The results obtained from the experiments show promising results, with an accuracy of over 93%. The proposed CNN-based approach provides a reliable and efficient tool for the classification of brain tumors, which can aid in the accurate diagnosis and treatment planning of patients.
  • Multibiometric Authentication System Using Gesture Recognition
    K.E. Purushothaman, A. Ashwini, L.K.Balaji Vignesh, A. Mahadevan
    2nd International Conference on Intelligent Cyber Physical Systems and Internet of Things Icoici 2024 Proceedings, 2024
    To successfully increase the security of the system in today's environment, person authentication is required. It is undeniably true that most individuals would prefer to be authenticated in the simplest and most transparent way possible, without having to remember a personal identification number. Identity verification is necessary for many everyday activities. Both the ear and the palm's features are recorded, and corresponding feature vectors are created. The score level values are obtained following the fusion process, and the values below the threshold values are deleted and the values over the threshold values are authenticated using the Gaussian Log Gabor filtering method. In this regard, a multi-biometric system based on a person's gesture can be employed. It uses the complementing physical and behavioral characteristics of the ear and palm, two separate biometrics. The transfer function is the log Gabor method. The system's reliability is effectively increased by the aforementioned technique. The main benefit was created based on the merging of two biometric systems to enhance performance as a whole. Various feature extraction, feature matching, and data fusion approaches are used to determine the saliency and correlation of the data that each sensor has collected. The outcomes also imply that the proposed algorithms outperform existing algorithms in terms of performance.
  • Enhanced Energy-Efficient Routing in WSNs: A Multipath Approach Using Binary Gray Wolf Optimization and Sugeno Fuzzy Logic
    Sivsakthiselvan S, M. Palanivelan, Purushothaman K E, Mohanraj S, Asokan V
    2024 International Conference on System Computation Automation and Networking Icscan 2024, 2024
  • Fault Detection in Solar Power System with Internet of Things using Multi resolution Sinusoidal Neural Network - Snow Geese Optimization Approach
    Pramod Kumar, K.E. Purushothaman, Arunmozhi R V, Jayachitra S, D. Leela Rani, S. Kaliappan
    4th International Conference on Sustainable Expert Systems Icses 2024 Proceedings, 2024
  • A Novel Weber Cross Information Sharing Deep Learning Encoder Decoder Model for Emotion Recognition Using Facial Expression
    Jeen Retna Kumar R, Berakhah.F. Stanley, Gnanaprakash V, Bini Palas P, Purusothaman K E, Joel Devadass Daniel D J
    2024 4th International Conference on Artificial Intelligence and Signal Processing Aisp 2024, 2024
  • Improving Microgrid Reliability and Efficiency Through Energy Storage Systems with a Pyramidal Dilation Attention Convolutional Neural Network for Renewable Energy Integration
    Bondu Vijayakumar, K.E. Purushothaman, Priyanka Khabiya, Akriti Garg, Rajesha N, S. Kaliappan
    4th International Conference on Sustainable Expert Systems Icses 2024 Proceedings, 2024
  • Innovative Urban Planning for Harnessing Blockchain and Edge Artificial Intelligence for Smart City Solutions
    K. E. Purushothaman, N. Ragavendran, S. P. Ramesh, V. Ganesh Karthikeyan, G. Uma Maheswari, R. Saravanakumar
    2nd International Conference on Intelligent Cyber Physical Systems and Internet of Things Icoici 2024 Proceedings, 2024
  • Latent Dirichlet Allocation for Topic Discovery and Segmentation in Big Data
    A. Clementking, S. Rani, R. Roseline, Purushothaman K E, G. Kavitha, S. Murugan
    2024 Global Conference on Communications and Information Technologies Gccit 2024, 2024
  • Leveraging blockchain technology to combat deception, deepfake, and counterfeit system
    T. Gopalakrishnan, Hayder M. A. Ghanimi, Tanweer Alam, K Sreekanth, K. E. Purushothaman, Sudhakar Sengan, Pankaj Dadheech
    Journal of Discrete Mathematical Sciences and Cryptography, 2024
  • Advancements in Cybersecurity Using Deep Learning Techniques Attack Detection for Trojan Horses
    Hosanna Princye P, Ahila A, A. Anna Lakshmi, N. Ragavendran, K. E. Purushothaman, G. Uma Maheswari, R. Saravanakumar
    2024 International Conference on Electrical Electronics and Computing Technologies Iceect 2024, 2024
  • Artificial Intelligence based real-time automatic detection and classification of skin lesion in dermoscopic samples using DenseNet-169 architecture
    A. Ashwini, K.E. Purushothaman, A. Rosi, T. Vaishnavi
    Journal of Intelligent and Fuzzy Systems, 2023
  • Performance observation of a concurrent compute-intensive vision system in a human-like autonomous intelligent robot
    V Velmurugan, L Sharmila, David Neels Ponkumar, K Giridhar Reddy, K.E Purushothaman, R Nanmaran, L Ranganathan
    Measurement Sensors, 2023
  • Smart Waste Collecting Robot Integration With IoT and Machine Learning
    S. Srinivasan, J Jegan Amarnath, Umamagewaran Jambulingam, K. E. Purushothaman
    2023 2nd International Conference on Smart Technologies for Smart Nation Smarttechcon 2023, 2023
  • Automatic Traffic Sign Board Detection from Camera Images Using Deep learning and Binarization Search Algorithm
    A Ashwini, K. E Purushothaman, Banu Priya Prathaban, M Jenath, R Prasanna
    2023 International Conference on Recent Advances in Electrical Electronics Ubiquitous Communication and Computational Intelligence Raeeucci 2023, 2023
  • Transmission Binary Mapping Algorithm with Deep Learning for Underwater Scene Restoration
    Ashwini A, Purushothaman K E, Gnanaprakash V, D Ferlin Deva Shahila, Vaishnavi T, Rosi A
    Proceedings of the International Conference on Circuit Power and Computing Technologies Iccpct 2023, 2023
  • The WhatsApp Based Cost-Effective Automation at Homes through Internet of Things
    Mohanraj S, Karthi J, Sridevi N, Purushothaman K E, Kalaivanan M, Sai Ganesh B
    IEEE 9th International Conference on Smart Structures and Systems Icsss 2023, 2023
  • Multiobjective optimization based on self-organizing Particle Swarm Optimization algorithm for massive MIMO 5G wireless network
    Kesavalu Elumalai Purushothaman, Velmurugan Nagarajan
    International Journal of Communication Systems, 2021
  • Evolutionary Multi-Objective Optimization Algorithm for Resource Allocation Using Deep Neural Network in 5G Multi-User Massive MIMO
    K. E. Purushothaman, V. Nagarajan
    International Journal of Electronics, 2021
  • Design and simulation of OFDMA transceiver for high speed 5g wireless network using immense PSO-GA
    Purushothaman K. E., Madhuvathani V., Nagarajan V.
    Proceedings of the 2019 IEEE International Conference on Communication and Signal Processing Iccsp 2019, 2019
  • Adaptive enhancement of low noise amplifier using cadence virtuoso tool
    K. Sakthidasan Sankaran, K. E. Purushothaman
    Proceedings 2017 2nd International Conference on Recent Trends and Challenges in Computational Models Icrtccm 2017, 2017
  • Designing an low noise amplifier with high bandwidth & low power consumption
    K. E. Purushothaman, V. Nagarajan
    International Conference on Communication and Signal Processing Iccsp 2016, 2016

RECENT SCHOLAR PUBLICATIONS

  • Precision Driven Sentiment and Topic Classification of News Articles using IndicBert Model (IBM)
    BP Prathaban, R Subash, B Sujin, KE Purushothaman, G Lakshmi
    2025 8th International Conference on Circuit, Power & Computing Technologies … , 2025
    2025
    Citations: 1
  • Analysis and Prediction of Road Accidents using Vision Transformer Model (VTM)
    BP Prathaban, D Saveetha, M Sangeetha, KE Purushothaman
    2025 8th International Conference on Circuit, Power & Computing Technologies … , 2025
    2025
  • HRL-GT: A Hybrid Reinforcement Learning and Game Theory Framework for Energy-Efficient Cluster Head Election and Routing in Underwater Sensor Networks
    S Sivsakthiselvan, M Palanivelan, N Sridevi, KE Purushothaman
    2025 2nd International Conference on Computing and Data Science (ICCDS), 1-6 , 2025
    2025
  • EA-DBSEP-IoUT: An Edge-Assisted Depth-Based Stable Election Protocol for Energy-Efficient Routing in IoUT
    S Sivsakthiselvan, S Pavithra, KE Purushothaman, S Samsudeen
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
    Citations: 1
  • Enhanced Variational Quantum Networks for EarlyAlzheimer’s Detection: a Quantum-Classical Approach
    S Samsudeen, MS Samsudeen, KE Purushothaman, P Radhakrishnan, ...
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
    Citations: 2
  • Enhanced Energy-Efficient Routing in WSNs: A Multipath Approach Using Binary Gray Wolf Optimization and Sugeno Fuzzy Logic
    S Sivsakthiselvan, M Palanivelan, KE Purushothaman, S Mohanraj, ...
    2024 International Conference on System, Computation, Automation and … , 2024
    2024
  • Enhancing cybersecurity in cloud computing and WSNs: A hybrid IDS approach
    K Sundaramoorthy, KE Purushothaman, JJ Sonia, N Kanthimathi
    Computers & Security 147, 104081 , 2024
    2024
    Citations: 12
  • Latent Dirichlet Allocation for Topic Discovery and Segmentation in Big Data
    A Clementking, S Rani, R Roseline, P KE, G Kavitha, S Murugan
    2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024
    2024
    Citations: 3
  • Fault Detection in Solar Power System with Internet of Things using Multi resolution Sinusoidal Neural Network-Snow Geese Optimization Approach
    P Kumar, KE Purushothaman, DL Rani, S Kaliappan
    2024 4th International Conference on Sustainable Expert Systems (ICSES … , 2024
    2024
  • Improving Microgrid Reliability and Efficiency Through Energy Storage Systems with a Pyramidal Dilation Attention Convolutional Neural Network for Renewable Energy Integration
    B Vijayakumar, KE Purushothaman, P Khabiya, A Garg, S Kaliappan
    2024 4th International Conference on Sustainable Expert Systems (ICSES … , 2024
    2024
    Citations: 1
  • Brain Tumor Classification Using CNNs
    D Saveetha, BP Prathaban, A Rashmi, KE Purushothaman
    2024 International Conference on Power, Energy, Control and Transmission … , 2024
    2024
    Citations: 1
  • Advancements in Cybersecurity Using Deep Learning Techniques Attack Detection for Trojan Horses
    A Ahila, AA Lakshmi, N Ragavendran, KE Purushothaman, ...
    2024 International Conference on Electrical Electronics and Computing … , 2024
    2024
    Citations: 3
  • Multibiometric Authentication System Using Gesture Recognition
    KE Purushothaman, A Ashwini, LKB Vignesh, A Mahadevan
    2024 Second International Conference on Intelligent Cyber Physical Systems … , 2024
    2024
  • Innovative urban planning for harnessing blockchain and edge artificial intelligence for smart city solutions
    KE Purushothaman, N Ragavendran, SP Ramesh, VG Karthikeyan, ...
    2024 Second International Conference on Intelligent Cyber Physical Systems … , 2024
    2024
    Citations: 8
  • The WhatsApp Based Cost-Effective Automation at Homes through Internet of Things
    S Mohanraj, J Karthi, N Sridevi, KE Purushothaman, M Kalaivanan, ...
    2023 9th International Conference on Smart Structures and Systems (ICSSS), 1-5 , 2023
    2023
    Citations: 2
  • Artificial Intelligence based real-time automatic detection and classification of skin lesion in dermoscopic samples using DenseNet-169 architecture
    A Ashwini, KE Purushothaman, A Rosi, T Vaishnavi
    Journal of Intelligent & Fuzzy Systems 45 (4), 6943-6958 , 2023
    2023
    Citations: 21
  • Smart Waste Collecting Robot Integration With IoT and Machine Learning
    S Srinivasan, JJ Amarnath, U Jambulingam, KE Purushothaman
    2023 Second International Conference On Smart Technologies For Smart Nation … , 2023
    2023
    Citations: 22
  • Transmission Binary Mapping Algorithm with Deep Learning for Underwater Scene Restoration
    A Ashwini, KE Purushothaman, V Gnanaprakash, T Vaishnavi, A Rosi
    2023 International Conference on Circuit Power and Computing Technologies … , 2023
    2023
    Citations: 8
  • Performance observation of a concurrent compute-intensive vision system in a human-like autonomous intelligent robot
    V Velmurugan, L Sharmila, DN Ponkumar, KG Reddy, KE Purushothaman, ...
    Measurement: Sensors 27, 100805 , 2023
    2023
    Citations: 4
  • Automatic traffic sign board detection from camera images using deep learning and binarization search algorithm
    A Ashwini, KE Purushothaman, BP Prathaban, M Jenath, R Prasanna
    2023 International Conference on Recent Advances in Electrical, Electronics … , 2023
    2023
    Citations: 26

MOST CITED SCHOLAR PUBLICATIONS

  • Multiobjective optimization based on self‐organizing Particle Swarm Optimization algorithm for massive MIMO 5G wireless network
    KE Purushothaman, V Nagarajan
    International Journal of Communication Systems 34 (4), e4725 , 2021
    2021
    Citations: 31
  • Automatic traffic sign board detection from camera images using deep learning and binarization search algorithm
    A Ashwini, KE Purushothaman, BP Prathaban, M Jenath, R Prasanna
    2023 International Conference on Recent Advances in Electrical, Electronics … , 2023
    2023
    Citations: 26
  • Evolutionary multi-objective optimization algorithm for resource allocation using deep neural network in 5G multi-user massive MIMO
    KE Purushothaman, V Nagarajan
    International Journal of Electronics 108 (7), 1214-1233 , 2021
    2021
    Citations: 24
  • Smart Waste Collecting Robot Integration With IoT and Machine Learning
    S Srinivasan, JJ Amarnath, U Jambulingam, KE Purushothaman
    2023 Second International Conference On Smart Technologies For Smart Nation … , 2023
    2023
    Citations: 22
  • Artificial Intelligence based real-time automatic detection and classification of skin lesion in dermoscopic samples using DenseNet-169 architecture
    A Ashwini, KE Purushothaman, A Rosi, T Vaishnavi
    Journal of Intelligent & Fuzzy Systems 45 (4), 6943-6958 , 2023
    2023
    Citations: 21
  • Enhancing cybersecurity in cloud computing and WSNs: A hybrid IDS approach
    K Sundaramoorthy, KE Purushothaman, JJ Sonia, N Kanthimathi
    Computers & Security 147, 104081 , 2024
    2024
    Citations: 12
  • Innovative urban planning for harnessing blockchain and edge artificial intelligence for smart city solutions
    KE Purushothaman, N Ragavendran, SP Ramesh, VG Karthikeyan, ...
    2024 Second International Conference on Intelligent Cyber Physical Systems … , 2024
    2024
    Citations: 8
  • Transmission Binary Mapping Algorithm with Deep Learning for Underwater Scene Restoration
    A Ashwini, KE Purushothaman, V Gnanaprakash, T Vaishnavi, A Rosi
    2023 International Conference on Circuit Power and Computing Technologies … , 2023
    2023
    Citations: 8
  • Prathaban M, Jenath and R Prasanna,“Automatic Traffic Sign Board Detection from Camera Images Using Deep learning and Binarization Search Algorithm”
    A Ashwini, KE Purushothaman, B Priya
    2023 International Conference in recent advances in Electrical, Electronics … , 2023
    2023
    Citations: 8
  • Adaptive enhancement of low Noise amplifier using Cadence Virtuoso tool
    KS Sankaran, KE Purushothaman
    2017 Second International Conference on Recent Trends and Challenges in … , 2017
    2017
    Citations: 5
  • Performance observation of a concurrent compute-intensive vision system in a human-like autonomous intelligent robot
    V Velmurugan, L Sharmila, DN Ponkumar, KG Reddy, KE Purushothaman, ...
    Measurement: Sensors 27, 100805 , 2023
    2023
    Citations: 4
  • Improved energy-saving multi-hop networking in wireless networks
    D David Neels Ponkumar, S Ramesh, KE Purushothaman, MR Arun
    International Conference On Innovative Computing And Communication, 587-599 , 2023
    2023
    Citations: 4
  • Latent Dirichlet Allocation for Topic Discovery and Segmentation in Big Data
    A Clementking, S Rani, R Roseline, P KE, G Kavitha, S Murugan
    2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024
    2024
    Citations: 3
  • Advancements in Cybersecurity Using Deep Learning Techniques Attack Detection for Trojan Horses
    A Ahila, AA Lakshmi, N Ragavendran, KE Purushothaman, ...
    2024 International Conference on Electrical Electronics and Computing … , 2024
    2024
    Citations: 3
  • Enhanced Variational Quantum Networks for EarlyAlzheimer’s Detection: a Quantum-Classical Approach
    S Samsudeen, MS Samsudeen, KE Purushothaman, P Radhakrishnan, ...
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
    Citations: 2
  • The WhatsApp Based Cost-Effective Automation at Homes through Internet of Things
    S Mohanraj, J Karthi, N Sridevi, KE Purushothaman, M Kalaivanan, ...
    2023 9th International Conference on Smart Structures and Systems (ICSSS), 1-5 , 2023
    2023
    Citations: 2
  • Design and Simulation of OFDMA Transceiver for High Speed 5G Wireless Network using Immense PSO-GA
    KE Purushothaman, V Madhuvathani, V Nagarajan
    2019 International Conference on Communication and Signal Processing (ICCSP … , 2019
    2019
    Citations: 2
  • Precision Driven Sentiment and Topic Classification of News Articles using IndicBert Model (IBM)
    BP Prathaban, R Subash, B Sujin, KE Purushothaman, G Lakshmi
    2025 8th International Conference on Circuit, Power & Computing Technologies … , 2025
    2025
    Citations: 1
  • EA-DBSEP-IoUT: An Edge-Assisted Depth-Based Stable Election Protocol for Energy-Efficient Routing in IoUT
    S Sivsakthiselvan, S Pavithra, KE Purushothaman, S Samsudeen
    2025 11th International Conference on Communication and Signal Processing … , 2025
    2025
    Citations: 1
  • Improving Microgrid Reliability and Efficiency Through Energy Storage Systems with a Pyramidal Dilation Attention Convolutional Neural Network for Renewable Energy Integration
    B Vijayakumar, KE Purushothaman, P Khabiya, A Garg, S Kaliappan
    2024 4th International Conference on Sustainable Expert Systems (ICSES … , 2024
    2024
    Citations: 1