GOVINDHARAJ I

Scopus Publications

An intensity-aware vision transformer framework for precise localization of vitreous hemorrhage in fundus imaging
M. Lavanya, R. Rampriya, Anandh Nagarajan, I. Govindharaj
International Ophthalmology, 2026
Learning feature dependencies for precise tumor region detection and segmentation in optical coherence tomography images
Anandh Nagarajan, T. Megala, A. Poongodai, P. Udayasankaran, I. Govindharaj, R. Shobana
International Ophthalmology, 2026
Structural fatigue modeling of cumulative mechanical stress in the athletic elbow using routine radiographs
I. Govindharaj, G. Michael, G. Karthick, R. Vimal Raja, B. Yuvaraj, E. Bharath
Journal of Orthopaedics, 2026
Efficient gastric tumor detection from endoscopic images using trans-mapped learning models
I. Govindharaj, Gnanajeyaraman Rajaram, S. Ravichandran, J. Viswanath, R. Elankavi, J. Raja
Biomedical Signal Processing and Control, 2026
Gastric cancer has emerged as a major health concern in recent years, often attributed to improper or unhealthy dietary habits. Early detection remains challenging due to the lack of identifiable symptoms in its initial stages, emphasizing the need for intelligent computational diagnostic methods. This study introduces the Inflate Region-based Tumor Recognition (IRTR) scheme, a novel approach leveraging endoscopy images and trans-mapped learning to detect inflated tumor regions with precision. The proposed scheme employs trans-mapping layers, which are trained to analyze inputs and outputs for identifying high and low-intensity feature regions. By focusing on external boundaries with elevated trans-intensity levels, the scheme effectively identifies regions exhibiting significant differences across the image. These mapped features are then utilized to train a model that repetitively processes high-to-low and low-to-high intensity transitions across input and output layers, enhancing the recognition of inflated tumor regions. Boundary differentiation, a key component of this approach, further refines detection precision from early endoscopic inputs. Evaluation results demonstrate that the IRTR scheme achieves superior performance, with an accuracy improvement of 9.38%, a precision increase of 12.04%, 9.69% in specificity and a mean error reduction of 11.04% for maximum intensity rates. This study underscores the potential of trans-mapped learning in advancing early gastric tumor detection.
Efficient data replication in distributed clouds via quantum entanglement algorithms
Prabhu Shankar B, RajKumar N, Jayavadivel Ravi, Viji C, Gobinath J, Govindharaj I, Dinesh Kumar K, Elango Muthusamy
Methodsx, 2026
In cloud computing, it remains difficult to make data available in a cloud service such that the data is replicated and maintained consistently across various data centers. Traditional replication systems are sufficient, even though they take too long to process, cause significant data transfers, and face problems with final data consistency. This work presents a new method named Quantum Entanglement-Based Replication Algorithm (QERA), which makes use of quantum entanglement to ensure quick and high-performance synchronization of cloud data across all nodes. In this proposed work, the QERA approach encodes data changes in the primary cloud node onto quantum states and entangled qubit pairs to the related replica nodes. As a result, any change is quickly shown on all replicas without the usual overhead and delay of message broadcasts. It simulates how QERA is designed to decrease latency, promote consistency, and make better use of resources in cloud environments. This paper creates a theoretical framework using IBM Qiskit and Microsoft Quantum Development Kit simulators to compare classical and quantum baseline algorithms. The results show that QERA may greatly enhance the way updates and replications are managed across many cloud systems. It demonstrates how QERA can ensure a very synchronized replication among the remote cloud nodes. Employs a qubit pair entangled to minimize latency and decrease bandwidth expenses as it goes through updates. Combines the idea of quantum teleportation with methods of non-invasive verification made to maintain the integrity of the state without altering the quantum system.
Femorotibial degeneration equilibrium analysis for objective and clinically interpretable knee osteoarthritis stratification
I. Govindharaj, Gnanajeyaraman Rajaram, K.K. Ezhilarasan, J. Viswanath
Journal of Orthopaedics, 2026
Attention-Enhanced LSTM Model for Task Offloading in Industrial Edge Computing
K. Udayakumar, K. Janani, M. Revathi, I. Govindharaj
Lecture Notes in Networks and Systems, 2026
RFF-JSS: A radiomic feature fusion and joint space segmentation framework for automated knee osteoarthritis assessment
K. Pugazharasi, Bhuvaneswari Srinivasan, Anandh Nagarajan, I. Govindharaj
Journal of Orthopaedic Reports, 2026
Knee osteoarthritis (KOA) is a leading cause of pain and functional disability worldwide. Radiographic severity grading using the Kellgren–Lawrence (KL) scale is widely adopted in clinical practice but remains subjective and susceptible to inter- and intra-observer variability, particularly when distinguishing adjacent grades. This study aims to develop an accurate, interpretable, and anatomically guided framework for automated KOA severity grading from plain knee radiographs. A novel Radiomic Feature Fusion and Joint Space Segmentation (RFF-JSS) framework is proposed for automated KOA severity assessment. The pipeline includes (i) standardized preprocessing of knee radiographs, (ii) anatomically informed tibiofemoral joint space segmentation using a U-Net model, (iii) IBSI-compliant multiscale radiomic feature extraction from medial and lateral compartments, (iv) PCA-based radiomic feature fusion for dimensionality reduction and redundancy suppression, and (v) ordinal-aware KOA severity classification using a Random Forest classifier. The framework was evaluated on 5,820 knee radiographs from two large public cohorts—the Osteoarthritis Initiative (OAI) and the Multicenter Osteoarthritis Study (MOST)—with stratified training, validation, and testing splits. The proposed RFF-JSS framework achieved an accuracy of 94.87%, precision of 95.12%, sensitivity of 94.68%, specificity of 96.10%, F1-score of 94.89%, ROC-AUC of 0.972, and a Quadratic Weighted Kappa (QWK) of 0.947. The method consistently outperformed state-of-the-art approaches, including ResNet-SVM, UNet-Radiomics, Deep-KOA, JSN-Net, RF-RFE, and CNN-KLNet. Ablation studies confirmed the critical contributions of joint space segmentation, compartment-wise analysis, feature standardization, and PCA-based radiomic fusion in improving classification robustness and reducing misclassification between adjacent KL grades. The RFF-JSS framework provides a robust, interpretable, and anatomically grounded solution for automated KOA severity grading from plain radiographs. By synergistically combining joint space segmentation with radiomic feature fusion and ordinal-aware classification, the proposed approach bridges the gap between high predictive performance and clinical interpretability, demonstrating strong potential for large-scale screening and clinical decision support in knee osteoarthritis assessment.
Feature pitched transformer model for automated diabetic retinopathy severity classification on fundus images
Allin Geo A.V., Lavanya M., Govindharaj I., Malathi V.
International Journal of Diabetes in Developing Countries, 2026
A Blockchain-Enabled Secure Federated Learning Framework for Decentralized AI Systems
K. Dinesh Kumar, Yaramati Surya Venkata Chaitanya, Lakkoju Hemanth Sai, I. Govindharaj, B. Prabhu Shankar, S. Edwin Raja
Proceedings of 6th International Conference on Expert Clouds and Applications Icoeca 2026, 2026
Federated Learning (FL) allows cooperative model training without the exchange of raw information, which makes it suitable in the privacy-intensive distributed setting. Nonetheless, traditional FL systems are based on centralized aggregation servers, and they are also assumed to participate honestly, which makes them vulnerable to model poisoning and free-rider attacks as well as transparency. This paper suggests TrustChain-FL, which is a federated learning framework based on blockchain with a secure federated learning system, which combines a permissioned blockchain with FL to provide decentralized trust, immutable model update records, and automatic validation via smart contracts. The results in experiments conducted in a simulated federated learning setting show that TrustChain-FL is effective in the scenario of mitigating malicious updates without losing model accuracy and convergence efficiency. The given framework can be applied to decentralized AI applications, including healthcare, smart cities, and industrial IoT. Experimental outcome reaches the best accuracy of up to 92.6% and huge resistance to poisoning attacks when compared to traditional FL Unlike current blockchain-assisted FL systems, TrustChain-FL is decoupled between update validation and aggregation with sparse permissioned consensus.
Association of plate working length and screw density with healing of comminuted distal femur fractures treated with locking plates
I. Govindharaj, G. Michael, E. Bharath, R. Rajesh, B. Yuvaraj, N. Sathish Kumar
Journal of Orthopaedic Reports, 2026
Prediction and Management of Post-Surgical Disease Recurrence
I Govindharaj, M. Retheesh, L. Kaleshwar Rao, B Prabhu Shankar, K Dinesh Kumar, K Udayakumar
2026 International Conference on Emerging Technologies and Future Innovations Etfi 2026, 2026
A cortical continuity–guided deep learning framework for detection and localization of subtle long bone fractures on radiographs
B. Prabhu Shankar, I. Govindharaj, E. Bharath, K. Dinesh Kumar, S. Palpandi, R. Rajesh
Journal of Orthopaedic Reports, 2026
SaaS-based Secure File Sharing with AI-driven Threat Detection
I Govindharaj, Tirumalaraju Akash Varma, Konduru Sai Hemanth Kumar, B Prabhu Shankar, K Dinesh Kumar, E Bharath
2026 International Conference on Emerging Technologies and Future Innovations Etfi 2026, 2026
Capsule network-based deep learning for early and accurate diabetic retinopathy detection
I. Govindharaj, R. Rampriya, G. Michael, S. Yazhinian, K. Dinesh Kumar, R. Anandh
International Ophthalmology, 2025
Advanced glaucoma disease segmentation and classification with grey wolf optimized U −Net++ and capsule networks
I. Govindharaj, W. Deva Priya, K. L. S. Soujanya, K. P. Senthilkumar, K. Shantha Shalini, S. Ravichandran
International Ophthalmology, 2025
Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2
I. Govindharaj, D. Santhakumar, K. Pugazharasi, S. Ravichandran, R. Vijaya Prabhu, J. Raja
Methodsx, 2025
Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification
Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J
Methodsx, 2025
Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis
Govindharaj I, Ramesh T, Poongodai A, Senthilkumar K. P, Udayasankaran P, Ravichandran S
Methodsx, 2025
Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning
Govindharaj I, Poongodai A, Gnanajeyaraman Rajaram, Santhakumar D, Ravichandran S, Vijaya Prabhu R, Udayakumar K, Yazhinian S
Methodsx, 2025
GSTLB-GPS Enabled Secured Software Defined Network using Transfer Learning and BlockChain Technology for Industrial IoT (IIoT)
S. Yazhinian, R. Sofia, D. Haripriya, D. Neelamegam, I. Govindharaj
Studies in Computational Intelligence, 2025
MediCon: A Lightweight, Reputation-Based Consensus Protocol to Allow Scalable and Secure Data Sharing in Healthcare
S. Edwin Raja, K. Dinesh Kumar, K. Manikandan, Senthil P, B. Prabhu Shankar, I. Govindharaj
Proceedings of 3rd International Conference on Sustainable Computing and Data Communication Systems Icscds 2025, 2025
Enhanced LCD Character Recognition Leveraging YOLOv11 and Modern Deep Learning Approaches
Dinesh Kumar K, Senthil P, Manoj Kumar D. S, S. Kishore Verma, J S Adeline Johnsana, Govindharaj I
2025 International Conference on Emerging Technologies in Engineering Applications Icetea 2025 Proceedings, 2025
Optimizing Urban Public Transportation Through AI-Based Bus Tracking and QR Code Ticketing
Rithik A, Prabhu Shankar B, Govindharaj I, Dinesh Kumar K, Vadhana Kumar M, David R
2025 2nd International Conference on Integration of Computational Intelligent System Icicis 2025, 2025
Comprehensive Threat Validation for Enhanced Network Security
K. Dinesh Kumar, Ch. Srisaiteja, Niranjan Peeka, I. Govindharaj, S. Edwin Raja, D. Dhinakaran
Proceedings of the 2025 3rd International Conference on Inventive Computing and Informatics Icici 2025, 2025
Farmyzaar: Secure Farmer Authentication in Agricultural Marketplace using Verhoeff Algorithm and OCR
Pavithra S, Vimal Raja. R, Kiruthika D, Kamali S, Mirudhula K, Govindharaj I
Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025
Fine-Tuning Faster R-CNN with Weighted ABC for Precision Detection of Grape Leaf Diseases
K. Balaji, T. Sivaprakash, R. Malathi, Govindharaj I, Prabhu Shankar B, Dinesh Kumar K
2025 2nd International Conference on Integration of Computational Intelligent System Icicis 2025, 2025
Enhanced Robustness in Lung Cancer Classification from CT Images Using Noise-Resistant Dynamic Integral Neural Networks
Govindharaj I, Michael G, Raja J, A.V. Allin Geo, Vimal Raja R, Dinesh Kumar K
2025 International Conference on Emerging Technologies in Engineering Applications Icetea 2025 Proceedings, 2025
Sensorless vector-controlled induction motor drives: Boosting performance with Adaptive Neuro-Fuzzy Inference System integrated augmented Model Reference Adaptive System
Govindharaj I, Dinesh Kumar K, Balamurugan S, Yazhinian S, Anandh R, Rampriya R, Karthick G, Michael G
Methodsx, 2024
Improving Robustness and Dynamic Performance of Sensor less Vector-Controlled IM Drives with ANFIS-Enhanced MRAS
Govindharaj I, Rampriya R, Balamurugan S, Yazhinian S, Dinesh Kumar K, Anandh R
International Journal of Electrical and Electronics Research, 2024
Enhancing Mango Quality Evaluation: Utilizing an MLP Model for Five-Class Severity Grading
I Govindharaj, Nitin Thapliyal, Manika Manwal, Vinay Kukreja, Rishabh Sharma
2024 International Conference on Innovations and Challenges in Emerging Technologies Icicet 2024, 2024
Onion Purple Blotch Disease Severity Grading: Leveraging a CNN-VGG16 Hybrid Model for Multi-Level Assessment
I Govindharaj, Nitin Thapliyal, Manisha Aeri, Vinay Kukreja, Rishabh Sharma
2024 International Conference on Innovations and Challenges in Emerging Technologies Icicet 2024, 2024
Improving Beech Bark Disease Classification: A Multiclass Approach with CNN-MLP Fusion
I Govindharaj, Saumitra Chattopadhyay, Kireet Joshi, Vinay Kukreja, Rishabh Sharma
2024 International Conference on Innovations and Challenges in Emerging Technologies Icicet 2024, 2024
Enhancing Rice Crop Health Assessment: Evaluating Disease Identification with a CNN-RF Hybrid Approach
I Govindharaj, Kapil Rajput, Navin Garg, Vinay Kukreja, Rishabh Sharma
2024 International Conference on Innovations and Challenges in Emerging Technologies Icicet 2024, 2024
Enhancing Food Supply Chain Transparency and Agricultural Practices through Blockchain Technology
Dinesh Kumar K, Vennila G, Manoj Kumar D S, J. Jeno Jasmine, Govindharaj I, Balamurugan S
2024 5th IEEE Global Conference for Advancement in Technology Gcat 2024, 2024
Diabetic Retinopathy Detection Using Capsule Network Modelled Deep Learning
Govindharaj I, Vijayarajeswari R, Anbuthiruvarangan K, Hannah Rose Esther T, Anandh R, Dinesh Kumar K
Proceedings of International Conference on Emerging Technologies and Innovation for Sustainability Emergin 2024, 2024
Elevating Medical Training: A Synergistic Fusion of AI and VR for Immersive Anatomy Learning and Practical Procedure Mastery
Harinee. S, Vimal Raja. R, Mugila. E, Govindharaj. I, Sanjaykumar. V, Ragavendhiran. T
2024 International Conference on System Computation Automation and Networking Icscan 2024, 2024
Early Melanoma Detection and Classification Using CNN and Confusion Matrix Analysis
Dinesh Kumar K, K. Jaya Deepthi, S. Saravanakumar, Balamurugan S, Govindharaj I, Pulikandla Akshay Reddeppa
2024 International Conference on System Computation Automation and Networking Icscan 2024, 2024
Advancing Glaucoma Detection: Synthetic Image Generation via Generative Adversarial Networks and Classification with Pretrained MobileNetV2
Ramprasad S R, Rampriya R, Poongodai A, Govindharaj I, Vimal Raja R, Yazhinian S
2024 International Conference on System Computation Automation and Networking Icscan 2024, 2024
Optimizing Flight Routes for Better Fuel Efficiency and Optimal Path using Grover's Algorithm & QAOA Algorithm - Quantum Computing
M. Imran Khan, I. Govindharaj, R. Sathishkumar, D. Jenifer, T. Maeghasree, K. Yohini
2024 International Conference on System Computation Automation and Networking Icscan 2024, 2024
Terrace garden using solar energy planting systems in IoT
, I. Govindharaj, Vimala D, , Shanmugapriya K, and
International Journal of Engineering and Advanced Technology, 2019
Effective information retrieval approach based on parallel matrix method and MapReduce framework
I. Govindharaj, D. Saravanan, R. Vaishali Lavanya, P. Dhivya, R. Jansi Rani, K. Prem Kumar
ACM International Conference Proceeding Series, 2015

RECENT SCHOLAR PUBLICATIONS

Efficient gastric tumor detection from endoscopic images using trans-mapped learning models
I Govindharaj, G Rajaram, S Ravichandran, J Viswanath, R Elankavi, ...
Biomedical Signal Processing and Control 118, 109646 , 2026
2026
A Cortical Continuity–Guided Deep Learning Framework for Detection and Localization of Subtle Long Bone Fractures on Radiographs
BP Shankar, I Govindharaj, E Bharath, KD Kumar, S Palpandi, R Rajesh
Journal of Orthopaedic Reports, 101025 , 2026
2026
Association of Plate Working Length and Screw Density with Healing of Comminuted Distal Femur Fractures Treated with Locking Plates
I Govindharaj, G Michael, E Bharath, R Rajesh, B Yuvaraj, NS Kumar
Journal of Orthopaedic Reports, 101048 , 2026
2026
Multimodal artificial intelligence for cross-population prediction of major adverse cardiovascular events: A multi-cohort external validation study
I Govindharaj, G Michael, PM Bala, S Balamurugan, R Sathishkumar, ...
International Journal of Cardiology Innovations, 100003 , 2026
2026
A Blockchain-Enabled Secure Federated Learning Framework for Decentralized AI Systems
KD Kumar, YSV Chaitanya, LH Sai, I Govindharaj, BP Shankar, SE Raja
2026 6th International Conference on Expert Clouds and Applications (ICOECA … , 2026
2026
Structural Fatigue Modeling of Cumulative Mechanical Stress in the Athletic Elbow Using Routine Radiographs
I Govindharaj, G Michael, G Karthick, RV Raja, B Yuvaraj, E Bharath
Journal of Orthopaedics , 2026
2026
Femorotibial Degeneration Equilibrium Analysis for Objective and Clinically Interpretable Knee Osteoarthritis Stratification
I Govindharaj, G Rajaram, KK Ezhilarasan, J Viswanath
Journal of Orthopaedics , 2026
2026
SaaS-based Secure File Sharing with AI-driven Threat Detection
I Govindharaj, TA Varma, KSH Kumar, BP Shankar, KD Kumar, E Bharath
2026 International Conference on Emerging Technologies and Future … , 2026
2026
Prediction and Management of Post-Surgical Disease Recurrence
I Govindharaj, M Retheesh, LK Rao, BP Shankar, KD Kumar, ...
2026 International Conference on Emerging Technologies and Future … , 2026
2026
An intensity-aware vision transformer framework for precise localization of vitreous hemorrhage in fundus imaging
M Lavanya, R Rampriya, A Nagarajan, I Govindharaj
International Ophthalmology 46 (1), 104 , 2026
2026
RFF-JSS: A Radiomic Feature Fusion and Joint Space Segmentation Framework for Automated Knee Osteoarthritis Assessment
K Pugazharasi, B Srinivasan, A Nagarajan, I Govindharaj
Journal of Orthopaedic Reports, 100899 , 2026
2026
Learning feature dependencies for precise tumor region detection and segmentation in optical coherence tomography images
A Nagarajan, T Megala, A Poongodai, P Udayasankaran, I Govindharaj, ...
International Ophthalmology 46 (1), 41 , 2025
2025
Citations: 2
Efficient data replication in distributed clouds via quantum entanglement algorithms
N RajKumar, J Ravi, C Viji, J Gobinath, I Govindharaj, D Kumar, ...
MethodsX, 103762 , 2025
2025
Citations: 1
Quantum-Accelerated Blockchain Framework for Identifying Counterfeit Detection in Global Supply Chains
N Rajkumar, G Nagarajan, C Viji, K Dinesh Kumar, I Govindharaj
2025 International Conference on Innovations and Emerging Technologies In AI … , 2025
2025
Optimized Faster R-CNN with Weighted ABC for High-Accuracy Gova Leaf Disease Identification
G Michael, S Ravichandran, J Sathiamoorthy, I Govindharaj, E Bharath
2025 International Conference on Innovations and Emerging Technologies In AI … , 2025
2025
Optimizing Urban Public Transportation Through AI-Based Bus Tracking and QR Code Ticketing
A Rithik, I Govindharaj, K Dinesh Kumar, M Vadhana Kumar, R David
2025 2nd International Conference on Integration of Computational … , 2025
2025
MediCon: A Lightweight, Reputation-Based Consensus Protocol to Allow Scalable and Secure Data Sharing in Healthcare
SE Raja, KD Kumar, K Manikandan, BP Shankar, I Govindharaj
2025 3rd International Conference on Sustainable Computing and Data … , 2025
2025
Citations: 1
Farmyzaar: Secure Farmer Authentication in Agricultural Marketplace using Verhoeff Algorithm and OCR
S Pavithra, D Kiruthika, S Kamali, K Mirudhula, I Govindharaj
2025 5th International Conference on Soft Computing for Security … , 2025
2025
Advanced glaucoma disease segmentation and classification with grey wolf optimized U− Net++ and capsule networks
I Govindharaj, W Deva Priya, KLS Soujanya, KP Senthilkumar, ...
International Ophthalmology 45 (1), 266 , 2025
2025
Citations: 9
Enhanced Robustness in Lung Cancer Classification from CT Images Using Noise-Resistant Dynamic Integral Neural Networks
I Govindharaj, G Michael, J Raja, AG AV, R Vimal Raja, K Dinesh Kumar
2025 International Conference on Emerging Technologies in Engineering … , 2025
2025

MOST CITED SCHOLAR PUBLICATIONS

Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2
I Govindharaj, D Santhakumar, K Pugazharasi, S Ravichandran, ...
MethodsX 14, 103116 , 2025
2025
Citations: 33
Capsule network-based deep learning for early and accurate diabetic retinopathy detection
I Govindharaj, R Rampriya, G Michael, S Yazhinian, K Dinesh Kumar, ...
International Ophthalmology 45 (1), 78 , 2025
2025
Citations: 24
Enhanced diabetic retinopathy detection using U-shaped network and capsule network-driven deep learning
I Govindharaj, A Poongodai, D Santhakumar, S Ravichandran, ...
MethodsX 14, 103052 , 2025
2025
Citations: 22
Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification
D Santhakumar, G Rajaram, R Elankavi, J Viswanath, I Govindharaj, ...
MethodsX 14, 103239 , 2025
2025
Citations: 12
Enhancing rice crop health assessment: evaluating disease identification with a CNN-RF hybrid approach
I Govindharaj, K Rajput, N Garg, V Kukreja, R Sharma
2024 International Conference on Innovations and Challenges in Emerging … , 2024
2024
Citations: 12
Onion purple blotch disease severity grading: leveraging a CNN-VGG16 hybrid model for multi-level assessment
I Govindharaj, N Thapliyal, M Aeri, V Kukreja, R Sharma
2024 International Conference on Innovations and Challenges in Emerging … , 2024
2024
Citations: 12
Grey wolf optimization technique with u-shaped and capsule networks-a novel framework for glaucoma diagnosis
I Govindharaj, T Ramesh, A Poongodai, P Udayasankaran, ...
MethodsX 14, 103285 , 2025
2025
Citations: 10
Advanced glaucoma disease segmentation and classification with grey wolf optimized U− Net++ and capsule networks
I Govindharaj, W Deva Priya, KLS Soujanya, KP Senthilkumar, ...
International Ophthalmology 45 (1), 266 , 2025
2025
Citations: 9
Sensorless vector-controlled induction motor drives: boosting performance with adaptive neuro-fuzzy inference system integrated augmented model reference adaptive system
I Govindharaj, D Kumar, S Balamurugan, S Yazhinian, R Anandh, ...
MethodsX 13, 102992 , 2024
2024
Citations: 9
Improving beech bark disease classification: a multiclass approach with CNN-MLP Fusion
I Govindharaj, S Chattopadhyay, K Joshi, V Kukreja, R Sharma
2024 International Conference on Innovations and Challenges in Emerging … , 2024
2024
Citations: 8
Hybrid Approach for Effective Segmentation and Classification of Glaucoma Disease Using UNet++ and CapsNet
G Iyyanar, K Gunasekaran, M George
Revue d'Intelligence Artificielle 38 (2), 613-621 , 2024
2024
Citations: 8
Enhancing Mango quality evaluation: utilizing an MLP model for five-class severity grading
I Govindharaj, N Thapliyal, M Manwal, V Kukreja, R Sharma
2024 International Conference on Innovations and Challenges in Emerging … , 2024
2024
Citations: 7
Optimizing Flight Routes for Better Fuel Efficiency and Optimal Path using Grover's Algorithm & QAOA Algorithm-Quantum Computing
MI Khan, I Govindharaj, R Sathishkumar, D Jenifer, T Maeghasree, ...
2024 International Conference on System, Computation, Automation and … , 2024
2024
Citations: 4
Enhancing Food Supply Chain Transparency and Agricultural Practices through Blockchain Technology
D Kumar, G Vennila, MK DS, JJ Jasmine, I Govindharaj, S Balamurugan
2024 5th IEEE Global Conference for Advancement in Technology (GCAT), 1-5 , 2024
2024
Citations: 4
Improving robustness and dynamic performance of sensor less vector-controlled IM drives with ANFIS-enhanced MRAS
I Govindharaj, R Rampriya, S Balamurugan, S Yazhinian, ...
International Journal of Electrical and Electronics Research 12 (3), 975-980 , 2024
2024
Citations: 3
Effective information retrieval approach based on parallel matrix method and MapReduce framework
I Govindharaj, D Saravanan, RV Lavanya, P Dhivya, RJ Rani, KP Kumar
Proceedings of the 2015 International Conference on Advanced Research in … , 2015
2015
Citations: 3
Learning feature dependencies for precise tumor region detection and segmentation in optical coherence tomography images
A Nagarajan, T Megala, A Poongodai, P Udayasankaran, I Govindharaj, ...
International Ophthalmology 46 (1), 41 , 2025
2025
Citations: 2
Comprehensive Threat Validation for Enhanced Network Security
KD Kumar, C Srisaiteja, N Peeka, I Govindharaj, SE Raja, D Dhinakaran
2025 3rd International Conference on Inventive Computing and Informatics … , 2025
2025
Citations: 2
Advancing Glaucoma Detection: Synthetic Image Generation via Generative Adversarial Networks and Classification with Pretrained MobileNetV2
SR Ramprasad, R Rampriya, A Poongodai, I Govindharaj, R Vimal Raja, ...
2024 International Conference on System, Computation, Automation and … , 2024
2024
Citations: 2
Efficient data replication in distributed clouds via quantum entanglement algorithms
N RajKumar, J Ravi, C Viji, J Gobinath, I Govindharaj, D Kumar, ...
MethodsX, 103762 , 2025
2025
Citations: 1

GOVINDHARAJ I

RESEARCH, TEACHING, or OTHER INTERESTS

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

MOST CITED SCHOLAR PUBLICATIONS