Sukumar Ponnusamy

@nandhaengg.org

Professor - Computer Science and Engineering
Nandha Engineering College (Autnomous)

Sukumar Ponnusamy


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https://researchid.co/sukumarwin

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Networks and Communications
35

Scopus Publications

509

Scholar Citations

11

Scholar h-index

12

Scholar i10-index

Scopus Publications

  • Plant Disease Prediction Using Ensemble Risk Scoring Engine
    Pavithra P, Sukumar P
    Proceedings of 2nd International Conference on Multi Agent Systems for Collaborative Intelligence Icmsci 2026, 2026
    Plant diseases are a significant menace to food security in the world since they largely decrease crop yield and agricultural output. Diagnostic methods that make use of traditional diagnostic techniques are usually time-consuming, subjective and error-prone because of manual observation. This paper will overcome these shortcomings by introducing an Ensemble Risk Scoring and Evaluation (ERSE) model, which utilizes machine learning algorithms to predict the early presence of the disease in plants based on environmental factors like temperature, humidity, rainfall and soil pH. The ERSE framework produces an output of a risk nature as opposed to the traditional binary classification methods, providing farmers and other parties within the agricultural industry with the opportunity to make decisions that are more balanced. The system combines several learning algorithms namely Random Forest, Logistic Regression and Isolation Forest into one integrated ensemble mechanism that combines the probability scores to provide better prediction reliability. Environmental factors that affect the development of the disease are analyzed to give more insight on the causal relationships. Moreover, the model includes data distribution, correlation, and performance measures visualization, which provides the comparative insights prior to and after the model implementation. It is proved by experimental results that the ERSE model enhances accuracy and robustness in prediction and risk-based scoring mechanism of ERSE model contributes to proactive intervention and long-term management of agriculture.
  • Knowledge-aware Attentional Neural Network based healthcare big data analytics optimized with Weighted Velocity-Guided Grey Wolf Optimization Algorithm
    N. Vasuki, C. Anand, P. Sukumar, V.Suresh Babu
    Biomedical Signal Processing and Control, 2025
  • Hybrid HGRN-SCSO technique for enhanced prediction of remaining useful life in EV batteries
    C. Pratheeba, P. Sukumar
    Electrical Engineering, 2025
  • Detection and diagnosis of cervical cancer in Pap smear cell images using hybrid CNN
    E. K. Arulkarthick, P. Sukumar
    Current Science, 2025
  • Efficient and secure task scheduling in cloud communication using hybrid convolutional neural network and enhanced encryption techniques
    Swaminathan G., Sukumar P.
    Akce International Journal of Graphs and Combinatorics, 2025
    Cloud communication is a combination of distributed computing and parallel computing. Task scheduling is a major challenge in cloud communications due to the NP-completeness of cloud systems. To address this, various swarm intelligence-based approximation techniques have been developed. This paper proposes a novel method for efficient task scheduling with improved security in cloud computing. A Hybrid Convolutional Neural Network with Long Short-Term Memory (HCNN-LSTM) optimized using FABOA is proposed for task scheduling to maximize throughput and minimize make span. Additionally, an improved random bit-stuffing technique with a modified RSA algorithm ensures secure data transmission. A novel Hybrid Convolutional Neural Network with Long Short-Term Memory (HCNN-LSTM) algorithm which is optimized using FABOA is proposed, which complicates readability. While the introduction outlines general cloud computing challenges, it lacks a focused literature review that identifies specific gaps in existing work and clearly justifies the need for the proposed HCNN-LSTM-FABOA system. Finally, our proposed approach is simulated under a cloudlet simulator and the evaluation results are analyzed to determine its performance. In addition to this, the proposed approach is compared with various other task scheduling-based approaches for various performance metrics, namely, resource utilization, response time, as well as energy consumption.
  • Optimizing energy efficiency in battery-powered electric vehicles: Leveraging Pontryagin’s minimum principle and model adaptive control
    Ravichandran V, Sukumar Ponnusamy
    Energy Sources Part A Recovery Utilization and Environmental Effects, 2025
    Electric vehicles, or EVs, are gaining more attention than ever before as a potential replacement for conventional vehicles. However, energy management has always been the primary and crucial concern in controlling EVs due to the current restricted energy density of batteries. This manuscript presents a Model Adaptive Control (MAC) utilizing Pontryagin’s Minimum Principle (PMP) to enhance the efficiency of electric vehicles (EVs) and introduces a structured continuous energy management approach through system development. The proposed method, named PMP-MAC, incorporates a Savitzky-Golay filter and the Erode-Gobichettipalayam smoother driving cycle to refine the control process. The major objective of the proposed approach is to enhance motor efficiency and improve the driving performance of electric vehicles. The MAC is used to control the reference current signal for regulating motor speed, while PMP is employed to solve energy efficiency problems. On the MATLAB platform, the proposed MAC is assessed and contrasted with other existing techniques. The proposed method shows better results in all existing such as Dynamic programming (DP), PMP, and Adaptive Optimization Control (AOC). The proposed method attains an efficiency of 95.23%, a total cost of 151.2 INR, and a computation time of 0.012s. The proposed PMP-MAC achieves better results compared to other existing methods.
  • DistilBERT-Powered Optimized Sentiment Analysis for Next-Generation Natural Language Processing
    S.R.Menaka, S.Mohanasundaram, P.Sukumar, S.M.Ramesh, Ravikumar Gurusamy, S.Hemalatha
    Proceedings of the 6th International Conference on Smart Electronics and Communication Icosec 2025, 2025
    This proposed system aims to assess the effectiveness and performance of DistilBERT, a streamlined transformer-based model, in sentiment classification tasks, in comparison to BERT. It centers on investigating whether DistilBERT can deliver comparable sentiment analysis results while minimizing computational resource demands, thereby make it suitable for real-time scenario and settings with limited resources. This study involves two distinct groups. Group 1 pertains to sentiment classification utilizing BERT, also with 26 samples. The power analysis is set at 80%, and the confidence interval at 95% the significance level at 0.05%, pertains to sentiment classification utilizing DistilBERT, which comprises 26 samples, while Group 2 pertains to sentiment classification utilizing DistilBERT, which comprises 26 samples. The DistilBERT model offers impressive accuracy while requiring much less computational power than BERT. DistilBERT's accuracy ranges between 91.34% to 97.89%, in contrast to BERT, which reaches an accuracy range of 88.12% and 96.45%. DistilBERT offers an effective approach to sentiment analysis, achieving impressive accuracy while requiring less computational power.
  • CNN-Faiss Pipeline for High Performance Animal Vocalization Retrieval and Classification
    S.M. Ramesh, Ravikumar Gurusamy, S.R. Menaka, S. Mohanasundaram, P. Sukumar, R. Keerthana
    Proceedings of the 6th International Conference on Electronics and Sustainable Communication Systems Icesc 2025, 2025
    Aim: To use deep learning methods for better animal vocalization classification and wildlife monitoring, such as autoencoder-based analysis, Faiss, animal2vec, and pretrained CNNs. Materials and Methods:The study analyzed and classified animal noises using bioacoustic data, autoencoderbased approaches, dual audio recording systems, self-supervised transformers (animal2vec), pre-trained CNNs, Faiss for similarity search, and ensemble methods. Group 1: The existing method ($\mathbf{C}$) analyzes animal vocalizations using spectrogrambased features and Mel-Frequency Cepstral Coefficients (MFCCs), with an accuracy of 85.3%, precision of 76.4%, recall of 72.1%, and an F1 score of 83.2%. Group 2: The proposed technique (Intervention) uses a multi-model approach that enhances accuracy by $\mathbf{9 5. 0 \%}(\mathbf{9. 7 \%}$ increase), precision by $\mathbf{8 7. 8 \%}$ ($\mathbf{1 1. 4 \%}$ increase), recall by $\mathbf{8 9. 5 \%}$ ($\mathbf{1 7. 4 \%}$ increase), and an F1 score by 88.6% (5.4 increase) by combining pre-trained CNNs with Faiss for similarity search. This improved performance shows notable progress in applications for species identification and real-time wildlife monitoring. Result: Using pre-trained models and ensemble approaches, the strategy increased the accuracy of (98.0%) classifying both common and unusual animal vocalizations, improved noise suppression, and was more adaptable to new species. Conclusion: The deep learning techniques showed scalability, efficiency, and adaptability, which made them an effective tool for species identification and wildlife monitoring in a variety of environments.
  • A Precision BMI Monitoring System with Real-Time Alerts using SHAP and XGBoost based Interpretability
    P. Sukumar, S. M. Ramesh, Ravikumar Gurusamy, S. R. Menaka, S. Mohanasundaram, P. Kalyanasundaram
    Proceedings of the 4th International Conference on Innovative Mechanisms for Industry Applications Icimia 2025, 2025
    The aim is to develop an Enhanced Sensitivity BMI Calculator that uses machine learning, specifically XGBoost, for accurate BMI predictions and SHAP for model transparency. The system provides real-time BMI analysis and personalized health notifications to improve individual health management. Group 1 estimates body fat percentage using Random Forest Regressor, while Group 2 develops a BMI prediction model with XGBoost, using SHAP for feature selection and interpretability, and delivers real-time personalized health feedback through real-time notifications. The model achieved high accuracy with MAE = 1.22, RMSE = 1.56, and R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.92, indicating strong performance in predicting BMI. SHAP analysis identified weight, age, and physical activity as the most influential factors in predictions. User feedback on the mobile app was highly positive, with ratings of 4.7/5 for accuracy and 4.8/5 for overall experience. In this work, it combines high-accuracy BMI predictions using XGBoost with transparent insights through SHAP (SHapley Additive exPlanations) analysis, offering real-time, personalized health notifications.
  • Hybrid SVM and Resonance Neural Network Model for Precision Personality Profiling
    V. Mythily, D. Vinoparkavi, P. Sukumar, Jafar Sathick R, Vinoth R, Vinitha M
    IEEE International Conference on Next Generation Information System Engineering Ngise 2025, 2025
    Personality Profiling in contemporary applications of psychology, human resources and marketing. Conventional mean, although powerful in isolating the first order personality traits can be extremely noisy so that inferencing more complex trait as a second or third- orders could easily lead to citation bias. Here, a new Hybrid System of SVM and Resonance Neural Network RNN based intelligent technique for secured personality is presented through this work. By using SVMs to perform feature separation efficiently and RNN for extracting temporal knowledge, we could identify the subtitle personality characteristics which can be missed by standalone models. The results showed that the model was able to classify with accuracy a sample of 92.1%, compared to around 50%-70%; and out-performed state-of-art SVM or RNN models on an extensive dataset, such as ImageNet for image classification purpose Furthermore, precision, recall and F1-score metrics were increased by at least 4.5%, demonstrating the robustness of the hybrid model in real-world practice. This suggests an application of hybrid machine learning architectures might further the state- of-the-art in personality profiling.
  • High-Performance Compact Antenna for Sub-6 GHz 5G MIMO Applications
    Rajendran Dhananjeyan, Mohit Pant, Kumarasamy Vishalatchi, Subramaniyan Janarthanan, Ponnusamy Sukumar, Dhanushkodi Siva Sundhara Raja, Dhandapani Rajeshkumar
    Progress in Electromagnetics Research C, 2025
  • COMPUTER-AIDED AUTOMATIC DETECTION AND DIAGNOSIS OF CERVICAL CANCER BY USING FEATURE MARKERS
    Computational Imaging and Analytics in Biomedical Engineering Algorithms and Applications, 2024
  • Enhancing the Predictive Accuracy of Lithium-Ion Battery Health in EV Using GBM-XGBoost
    Jaidev Kumar, N Saikumari, Soumya Mishra, P. Sukumar, S Vinayagam, Anil Kumar Lamba
    2024 3rd International Conference for Advancement in Technology Iconat 2024, 2024
  • Optimizing Fertilizer Recommendations for Crops Using Gradient Boosted Decision Trees with Logistic Regression and GA
    R M Lavanya, D J Samatha Naidu, Laxmi Biban, P Sukumar, N. Srija, M. Sucharitha
    2024 Global Conference on Communications and Information Technologies Gccit 2024, 2024
  • Object Recognition and Tracking System to Assist Visually Impaired: A Neural Network-Based Deep RBM Technique
    Sonal Patil, Shashishekhar Ramagundam, P. Sukumar, Mohiuddin Ali Khan, Nisha Deepak Patil, Neerav Nishant
    1st International Conference on Electronics Computing Communication and Control Technology Iceccc 2024, 2024
  • Enhancing Energy Efficiency and Security in IoTDriven Smart Cities Using Hybrid GAN-ICA Framework
    Mohammed Hafeezuddin, Archana Jadhav, P. Renuka, P Sukumar, Manasi Vyankatesh Ghamande, Kusuma Rajasekhar
    2024 Global Conference on Communications and Information Technologies Gccit 2024, 2024
  • Hyperbolic Hopfield Neural Network for Enhanced Solar Power Generation Forecasting
    Raj Kumar Gupta, Naveen K N, P Sukumar, C. Yamini, Raghapriya NR, Vijay Kumar Dwivedi
    4th IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2024, 2024
  • Advanced Fake Review Detection via Aspect Extraction and TPA-BiLSTM-CSSA
    Nilam Thakkar, Arvind Kumar, P. Sukumar, Deepika G. Sarode, Harshal Patil, E. Vijayakumar
    2nd IEEE International Conference on Data Science and Network Security Icdsns 2024, 2024
  • Monitoring in-Vehicle Air Quality in Real Time Through IoT and Enhanced Deep Learning Models
    K Prashanth Kumar, Jaidev Kumar, Neeru Malik, Archana Jadhav, P. Sukumar, Neerav Nishant
    2024 1st International Conference on Software Systems and Information Technology Ssitcon 2024, 2024
  • A Novel Integrated System for Forest Fire Detection using Multiple Adaptive Reduced KELM Models
    Deepak Kholiya, Mummidi Rachel, Arivarasan S, P. Sukumar, K Jayaram Kumar, T. Aswini Devi
    2nd IEEE International Conference on Data Science and Network Security Icdsns 2024, 2024
  • Enhancing Fake Review Detection: A Hierarchical Graph Attention Network Approach Using Text and Ratings
    T. Anuprathibha, RVS Praveen, Jayanth H, P Sukumar, G. Suganthi, T Ravichandran
    2024 Global Conference on Communications and Information Technologies Gccit 2024, 2024
  • Intelligent Farming in Rural Areas: CBGRU-Based Smart Agriculture and Precision Solutions
    M. Laxmi, Tamilselvan V, Ramesh C, K. Renganathan, P. Sukumar, S. Kaliappan
    4th IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2024, 2024
  • Retraction Note to: Computer aided innovation method for detection and classification of cervical cancer using ANFIS classifier (Journal of Ambient Intelligence and Humanized Computing, (2021), 12, 6, (6231-6240), 10.1007/s12652-020-02191-9)
    Sukumar Ponnusamy, Ravi Samikannu, Sampath Kumar Venkatachary, Sharmila Sukumar, Rohini Ravi
    Journal of Ambient Intelligence and Humanized Computing, 2023
  • Prediction of Rainfall Analysis Using Logistic Regression and Support Vector Machine
    R Praveena, T R Ganesh Babu, M Birunda, G Sudha, P Sukumar, J Gnanasoundharam
    Journal of Physics Conference Series, 2023
  • Classification of WBC cell classification using fully connected convolution neural network
    K Gokul Kannan, T R Ganesh Babu, R Praveena, P Sukumar, G Sudha, M Birunda
    Journal of Physics Conference Series, 2023
  • Impurity Monitoring using IOT
    Sarathkumar D, Srinivasan Murugesan, P Sukumar, Raymon Antony Raj, Sampath Kumar Venkatachary, Leo John Baptist Andrews, Dishore Shunmugham Vanaja
    2023 International Conference on Energy Materials and Communication Engineering Icemce 2023, 2023
  • Detection and classification of cervical cancer images using CEENET deep learning approach
    T.G. Subarna, P. Sukumar
    Journal of Intelligent and Fuzzy Systems, 2022
  • Computer aided innovation method for detection and classification of cervical cancer using ANFIS classifier
    Sukumar Ponnusamy, Ravi Samikannu, Sampath Kumar Venkatachary, Sharmila Sukumar, Rohini Ravi
    Journal of Ambient Intelligence and Humanized Computing, 2021
  • Cascade network based multitask perspective designing agribot
    Journal of Critical Reviews, 2019
  • Computer aided detection and classification of Pap smear cell images using principal component analysis
    Ponnusamy Sukumar, Samikannu Ravi
    International Journal of Bio Inspired Computation, 2018
  • Computer aided detection of cervical cancer using pap smear images based on adaptive neuro fuzzy inference system classifier
    P. Sukumar, R. K. Gnanamurthy
    Journal of Medical Imaging and Health Informatics, 2016
  • Design and implementation of a microcontroller based buck boost converter as a smooth starter for permanent magnet motor
    S. Ravi, Vitaliy Mezhuyev, K. Iyswarya Annapoorani, P. Sukumar
    Indonesian Journal of Electrical Engineering and Computer Science, 2016
  • Computer aided screening of cervical cancer using random forest classifier
    Research Journal of Pharmaceutical Biological and Chemical Sciences, 2016
  • Computer Aided Detection of Cervical Cancer Using Pap Smear Images Based on Hybrid Classifier
    International Journal of Applied Engineering Research, 2015
  • Segmentation and abnormality detection of cervical cancer cells using fast ELM with particle swarm optimization
    P. Sukumar, R.K. Gnanamurthy
    Genetika, 2015

RECENT SCHOLAR PUBLICATIONS

  • Plant Disease Prediction Using Ensemble Risk Scoring Engine
    P Pavithra, P Sukumar
    2026 Second International Conference on Multi-Agent Systems for … , 2026
    2026
  • Knowledge-aware Attentional Neural Network based healthcare big data analytics optimized with Weighted Velocity-Guided Grey Wolf Optimization Algorithm
    N Vasuki, C Anand, P Sukumar, VS Babu
    Biomedical Signal Processing and Control 110, 108160 , 2025
    2025
    Citations: 2
  • Efficient and secure task scheduling in cloud communication using hybrid convolutional neural network and enhanced encryption techniques
    SG Sukumar P
    AKCE INTERNATIONAL JOURNAL OF GRAPHS AND COMBINATORICS 22 (2), 1-17 , 2025
    2025
  • DistilBERT-Powered Optimized Sentiment Analysis for Next-Generation Natural Language Processing
    SR Menaka, S Mohanasundaram, P Sukumar, SM Ramesh, R Gurusamy, ...
    2025 6th International Conference on Smart Electronics and Communication … , 2025
    2025
  • CNN-Faiss Pipeline for High Performance Animal Vocalization Retrieval and Classification
    SM Ramesh, R Gurusamy, SR Menaka, S Mohanasundaram, P Sukumar, ...
    2025 6th International Conference on Electronics and Sustainable … , 2025
    2025
  • A Precision BMI Monitoring System with Real-Time Alerts using SHAP and XGBoost based Interpretability
    P Sukumar, SM Ramesh, R Gurusamy, SR Menaka, S Mohanasundaram, ...
    2025 4th International Conference on Innovative Mechanisms for Industry … , 2025
    2025
  • Detection and diagnosis of cervical cancer in Pap smear cell images using hybrid CNN.
    EK Arulkarthick, P Sukumar
    Current Science (00113891) 129 (3) , 2025
    2025
  • Hybrid HGRN-SCSO technique for enhanced prediction of remaining useful life in EV batteries
    C Pratheeba, P Sukumar
    Electrical Engineering 107 (4), 5311-5323 , 2025
    2025
    Citations: 6
  • Hybrid SVM and Resonance Neural Network Model for Precision Personality Profiling
    V Mythily, D Vinoparkavi, P Sukumar, J Sathick
    2025 International Conference on Next Generation Information System … , 2025
    2025
  • A novel approach to constructing features and models for intrusion detection systems using SAE-ELM model
    DP Singh, VW Gangane, P Sukumar, J Kaushal, N Nishant, H Patil
    Hybrid and Advanced Technologies, 401-406 , 2025
    2025
    Citations: 1
  • High-Performance Compact Antenna for Sub-6 GHz 5G MIMO Applications
    DRK Rajendran Dhananjeyan, Mohit Pant, Kumarasamy Vishalatchi, Subramaniyan ...
    Progress In Electromagnetics Research C 157, 57-63 , 2025
    2025
    Citations: 5
  • Optimizing energy efficiency in battery-powered electric vehicles Leveraging Pontryagin s minimum principle and model adaptive control
    SP Ravichandran V
    ENERGY SOURCES, PART A: RECOVERY, UTILIZATION, AND ENVIRONMENTAL EFFECTS 47 (2) , 2025
    2025
    Citations: 1
  • Malware detection and prevention using machine learning
    V Mythily, P Sukumar, V Akshaya, S Dinesh, M Nandhini
    Challenges in Information, Communication and Computing Technology, 564-569 , 2024
    2024
  • Diagnosis of autism spectrum disorder using deep learning with natural language processing
    GV Londhe, P Sukumar, B Krishnan, BY Supriya, R Karthik, C Hemalatha
    Challenges in information, communication and computing technology, 402-406 , 2024
    2024
    Citations: 4
  • IoT-powered street light management: Enhancing fault detection and reporting
    P Sukumar, S Jayasurya, M Rohith, ES Premnath, K Sugumar, V Mythily
    Challenges in Information, Communication and Computing Technology, 136-140 , 2024
    2024
    Citations: 2
  • Improved plant leaf disease classification using meta-heuristic algorithm based deep learning
    N Pravin, P Sukumar, S Karuppusamy, V Mythily, S Kavitha, ...
    Challenges in Information, Communication and Computing Technology, 365-369 , 2024
    2024
    Citations: 1
  • Intelligent Farming in Rural Areas: CBGRU-Based Smart Agriculture and Precision Solutions
    M Laxmi, V Tamilselvan, C Ramesh, K Renganathan, P Sukumar, ...
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024
  • Hyperbolic Hopfield Neural Network for Enhanced Solar Power Generation Forecasting
    RK Gupta, KN Naveen, P Sukumar, C Yamini, NR Raghapriya, ...
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024
    Citations: 6
  • Enhancing energy efficiency and security in iotdriven smart cities using hybrid gan-ica framework
    M Hafeezuddin, A Jadhav, P Renuka, P Sukumar, MV Ghamande, ...
    2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024
    2024
    Citations: 1
  • Enhancing Fake Review Detection: A Hierarchical Graph Attention Network Approach Using Text and Ratings
    T Anuprathibha, RVS Praveen, P Sukumar, G Suganthi, T Ravichandran
    2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024
    2024
    Citations: 89

MOST CITED SCHOLAR PUBLICATIONS

  • Enhancing Fake Review Detection: A Hierarchical Graph Attention Network Approach Using Text and Ratings
    T Anuprathibha, RVS Praveen, P Sukumar, G Suganthi, T Ravichandran
    2024 Global Conference on Communications and Information Technologies (GCCIT … , 2024
    2024
    Citations: 89
  • Computer aided detection of cervical cancer using pap smear images based on adaptive neuro fuzzy inference system classifier
    P Sukumar, RK Gnanamurthy
    Journal of Medical Imaging and Health Informatics 6 (2), 312-319 , 2016
    2016
    Citations: 77
  • Computer aided detection of cervical cancer using Pap smear images based on hybrid classifier
    P Sukumar, RK Gnanamurthy
    International Journal of Applied Engineering Research, Research India … , 2015
    2015
    Citations: 35
  • Prediction of rainfall analysis using logistic regression and support vector machine
    R Praveena, TRG Babu, M Birunda, G Sudha, P Sukumar, ...
    Journal of Physics: Conference Series 2466 (1), 012032 , 2023
    2023
    Citations: 26
  • Design and Implementation of a Microcontroller Based Buck Boost Converter as a Smooth Starter for Permanent Magnet Motor
    S Ravi, V Mezhuyev, KI Annapoorani, P Sukumar
    Indonesian Journal of Electrical Engineering and Computer Science 1 (3), 566-574 , 2016
    2016
    Citations: 21
  • Computer Aided Screening of Cervical Cancer Using Random Forest Classifier
    PSARK Gnanamurthy
    Research Journal of Pharmaceutical, Biological and Chemical Sciences 7 (1 … , 2016
    2016
    Citations: 19
  • Computer Aided Screening of Cervical Cancer Using Random Forest Classifier
    P Sukumar, RK Gnanamurthy
    Research Journal of Pharmaceutical, Biological and Chemical Sciences 7 (1 … , 2016
    2016
    Citations: 18
  • Error Detection and Correction in SRAM Cell Using DecimalMatrix Code
    T Maheswari, P Sukumar
    IOSR Journal of VLSI and Signal Processing (IOSR-JVSP) 5 (1), 09-14 , 2015
    2015
    Citations: 15
  • Detection and classification of cervical cancer images using CEENET deep learning approach
    TG Subarna, P Sukumar
    Journal of Intelligent & Fuzzy Systems 43 (3), 3695-3707 , 2022
    2022
    Citations: 13
  • Segmentation and abnormality detection of cervical cancer cells using fast elm with particle swarm optimization
    P Sukumar, RK Gnanamurthy
    Genetika 47 (3), 863-876 , 2015
    2015
    Citations: 12
  • Classification of WBC cell classification using fully connected convolution neural network
    K Gokul Kannan, TR Ganesh Babu, R Praveena, P Sukumar, G Sudha, ...
    Journal of Physics: Conference Series 2466 (1), 012033 , 2023
    2023
    Citations: 11
  • Design and development of microcontroller-based temperature monitoring and control system for power plant generators
    S Ponnusamy, R Samikannu, BA Tlhabologo, W Ullah, S Murugesan
    IOP Conference Series: Materials Science and Engineering 1055 (1), 012158 , 2021
    2021
    Citations: 11
  • Weed Detection Using Image Processing By Clustering Analysis
    P Sukumar, S Ravi
    International Journal of Emerging Technologies in Engineering Research … , 2016
    2016
    Citations: 10
  • Highly Secured Indoor Outdoor Localization forE- Hostel Management
    PS K.Sabeha
    Journal of Network Communications and Emerging Technologies (JNCET) 5 (1), 30-34 , 2015
    2015
    Citations: 9
  • Retinal lesion detection by using points of interest and visual dictionaries
    C Meganathan, P Sukumar
    International Journal of Advanced Research in Electronics and Communication … , 2013
    2013
    Citations: 9
  • Computer aided detection and classification of Pap smear cell images using principal component analysis
    P Sukumar, S Ravi
    International Journal of Bio-Inspired Computation 11 (4), 257-266 , 2018
    2018
    Citations: 8
  • IOT Based Efficient Vehicle Location Help Line System Using NFC
    P Sukumar, S Ravi
    International Journal of Emerging Technologies in Engineering Research … , 2016
    2016
    Citations: 8
  • Power Reduction for Sequential Circuit using Merge Flip-Flop Technique
    P S.Tamilselvi, Sukumar
    International Journal of Emerging Technology and Advanced Engineering(IJETAE … , 2014
    2014
    Citations: 8
  • Highly Secured System to Find the Improper Impression of Fingerprints in Hostel
    PS K.Sabeha
    International Journal for Scientific Research & Development 3 (11), 6 , 2016
    2016
    Citations: 7
  • Asynchronous Transfer Mode Implementation Using Z-T CAM
    PS M.Kangavalli
    International Journal of Engineering Research-Online 3 (2), 155 – 162 , 2015
    2015
    Citations: 7