R.Rajesh

@veltech.edu.in

Assistant Professor, Department of Computer Science and Engineering, School of Computing
Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology

R.Rajesh


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https://researchid.co/rajeshrangan
Working as Assistant Professor in Department of computer Science and Engineering, Vel Tech Rangarajan R&D Institute of Science and Technology. Received his Ph.D degree in Information Technology in Annamalai University. Published eight research papers in reputed International Journals and five International conferences. Received funds for organizing Seminar and conference from ISRO and DHR. Acted as one of the speakers and organized various Seminars and Workshop. Main research work focuses on Inter of Things and Wireless Sensor Networks. Has 9 years of teaching experience and he has guided more than 10 Under graduations and Post graduations.

EDUCATION

B.E -Computer Science and Engineering from Anna University in 2006
M.Tech -Information Technology from Sathyabama University in 2023
Technology from Annamalai University in 2023
22

Scopus Publications

264

Scholar Citations

7

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Leveraging the ConvNeXt-L Model for Tomato Leaf Disease Classification
    R. Rajesh, P. Shanmugam, A. Rajasekar, A. Chinnappa, N. Ramya, K. Theivanai
    Proceedings of 2nd International Conference on Visual Analytics and Data Visualization Icvadv 2026, 2026
    Accurate identification and classification of disease symptoms on the tomato leaves, is a vital part of the development of phyllobiological health and complementary agronomical productivity. This study proposes a carefully crafted deep learning architecture which is designed to complement detection and categorization of the most common tomato leaf diseases. The methodology begins with a preprocessing step which is performed separately by a U-Net segmentation network, which isolates the salient regions of the leaves and eliminates non-essential artefacts. Subsequently, it extracts discriminative features using ResNet50 backbone which is famous for its ability to extract multi-scale hierarchical representations. The feature maps that are generated are eventually fed into a ConvNeXt-L classifier, which is responsible for differentiating a wide range of classes of diseases. The proposed framework is tested with a dataset of images of tomato leaf disease, taken from Mendeley, containing 18,000 images with a clear labeling. The integrated model has a high accuracy of 98.12%, which shows its good potential for reliable disease classification. In addition, the comparison with other architectures that are well-known like InceptionV3 and DenseNet121, the suggested approach gives superior performance in terms of accuracy and feature discrimination.
  • SecDL-Fuse: A Hybrid Secure Deep Learning Framework for Industrial Cybersecurity Using Transformer-Enhanced CNN and LSTM-GRU Fusion
    P. Hemalatha, R. Rajesh, R. Vijayabharathi, K. Chandra Sekhar, J. Raja, M. Ravichandran
    Lecture Notes in Networks and Systems, 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
  • 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
  • Forecasting Soil Moisture Dynamics from SMAP Observations via Signal Decomposition
    D. Dhinakaran, V. Vijayalakshmi, S. Palpandi, R. Rajesh, D. Selvaraj, A. Rehash Rushmi Pavitra, Ahmad Salah
    Earth Systems and Environment, 2026
  • A Hybrid Expert System Using Symbolic Reasoning and Neural Networks for Predictive Maintenance in Mechatronic Systems
    Venkatesh S, Chandravadhana S, Rajesh R, Sagar Imambi S, Arivazhagan D, Vedaraj M
    Journal of Machine and Computing, 2025
    Predictive maintenance (PdM) in mechatronic systems demands high-precision failure prediction and interpretability for real-time operational decisions. This study presents a hybrid expert system integrating symbolic reasoning and Deep Neural Networks (DNNs) to enhance predictive accuracy and semantic traceability. The symbolic layer consists of 42 fuzzy inference rules, enabling domain expert interpretability, while the neural network layer comprises a 4-layer feedforward architecture with 128-64-32-1 units using ReLU and sigmoid activations. Experiments were conducted on a real-world dataset, and the hybrid model achieved an accuracy of 96.8%, a precision of 94.22%, and a recall of 97.31%, outperforming conventional Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) models, and rule-based systems by margins of 3.2–7.8%. The proposed method reduced false positives by 21.4% and improved time-to-failure prediction by 18.7% compared to standalone models. Maintenance scheduling optimized using the proposed model yielded a 14.5% reduction in unplanned downtime. The hybrid inference strategy not only improved prediction granularity but also supported rule-based diagnostics. This framework significantly advances predictive intelligence in safety-critical mechatronic domains.
  • Coordinate Memory Deduplication and Partition for Improving Cloud Efficiency
    R. Premalatha, R. Rajesh
    Aip Conference Proceedings, 2025
  • Enhancing radiographic image interpretation: WARES-PRS model for knee bone tumour detection
    Rahamathunnisa Usuff, Sudhakar Kothandapani, Rajesh Rangan, Saravanan Dhatchnamurthy
    Network Computation in Neural Systems, 2025
    The early diagnosis of tumour is significant in biomedical research field to lower the severity level and restrict the process extension from cancer. Moreover, the detection of early sign of cancer is undertaken with extensive research efforts that dedicated to the disclosure and recognition of tumours. However, the limited data size as well as diverse appearance of images lowered the detection performance and failed to detect complex stage of tumour. So to solve these issues, a Weighted Adaptive Random Ensemble Support Vector-based Partial Reinforcement Search (WARES-PRS) algorithm is proposed that detected bone lesions accurately and also predicted the severity level stage efficiently. Further, the detection is performed with varied stages to diminish the presence of noise and undertaken effective classification. The performance is validated with CNUH dataset that enhanced image pre-processing tasks. Despite the proposed method uncover the mutual relationships between each pixel's local texture and the overall image's global context. The detection and classification efficiency is validated with various measures and the experimental results revealed that the detection accuracy is enhanced for the proposed approach by 98.5%. The outcomes of our study have exhibited a substantial contribution to assisting physicians in the detection of knee bone tumours.
  • Dynamic Multi-Agent Reinforcement Learning Based Load Balancing on Software Defined Networking
    S. Wilson Prakash, S. Usharani, R. Rajesh, Rajkumar K
    2025 International Conference on Networks and Cryptology Netcrypt 2025, 2025
    Cloud computing provides on-demand access to computing re-sources via the internet, but efficient resource utilization and traffic man-agement remain challenging due to dynamic workloads. This paper proposes a Dynamic Multi-Agent Reinforcement Learning (MARL)-based Load Balancing (DA-LB) algorithm for Software-Defined Networking (SDN)-enabled cloud data centers. Unlike existing heuristic or single-agent reinforcement learning approaches, DA-LB leverages decentralized cooperation among MARL agents to achieve adaptive load balancing, leveraging SDN's global visibility for efficient Virtual Machine (VM) migration. The algorithm dy-namically predicts overloaded VMs, minimizes migration time, and adapts to traffic fluctuations. Experimental results demonstrate a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{30 \%}$</tex> reduction in migration time and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{25 \%}$</tex> improvement in resource utilization compared to Multipath TCP (MPTCP) and heuristic methods. Key innovations include: •A Decentralized Partially Observable Markov Decision Process (Dec-POMDP) framework for scalable multi-agent coordination. •Integration of actor-critic algorithms with epsilon-greedy exploration and parameter sharing for robust policy learning. •SDN-driven global state awareness to optimize VM placement.
  • Quantum-Enhanced Deep Learning for Predictive Diagnostics and Personalized Treatment in Smart Healthcare Systems
    R. Rajesh, P. Hemalatha, R. Vijayabharathi, S. Bargunan, S. R. Ramprasad, J. Raja
    Proceedings of 5th International Conference on Pervasive Computing and Social Networking Icpcsn 2025, 2025
    The synergy between quantum computing and deep learning holds revolutionary promise in facilitating smart healthcare by addressing problems in predictive diagnosis, realtime patient tracking, and personalized therapy. Deep learning algorithms such as CNNs and RNNs have scalability and efficiency limitations in processing clinical data with high dimensionality. Their limitations can be addressed by quantum computing through an inbuilt parallelism. This work suggests that Quantum-Enhanced Deep Learning for Smart Healthcare (QEDL-Health) should marry classical deep learning with quantum algorithms to revamp paradigms in healthcare. QEDL-Health applies quantum neural networks (QNNs) with quantum gates (Pauli-X, Hadamard, CNOT) to perform encoding and feature extraction efficiently. Model parameters are trained by quantum variational circuits (QVCs), while quantum support vector machines (QSVMs) diagnose diseases with better accuracy. IoT-generated vitals in real-time tracking are processed by quantum principal component analysis (QPCA), while personalized treatment is created by quantum approximate optimization algorithms (QAOAs). The system applies quantum Fourier transforms (QFTs) and Grover’s search algorithm to process efficiently. Experimental results in MIMIC-III, TCGA, and COVID-19 datasets confirm dominance by improving diagnostic correctness by 15% while computation time is decreased by 40% in genomic data processing compared to classical methods. Experimental results confirm that comparative evaluation establishes that conventional methods in deep learning have scalability limitations in efficiency and performance in intricate tasks in disease detection (such as cancer) and in tracking in real-time. This work bridges quantum computing with AI to lay the foundations for developing efficient, scalable, and intelligent healthcare systems to detect diseases earlier in time to reduce costs and improve patient outcomes.
  • YOLOX Driven Smart Surveillance for Real Time Intelligent Object Detection and Anomaly Monitoring
    S. Usharani, R. Rajesh, D.Annal Priyadarshini, R. Vijayabharathi, P.Manju Bala, R. Muthukumaran
    2025 5th International Conference on Intelligent Technologies Conit 2025, 2025
  • Detecting Malicious Data in Agricultural Systems: An Integrated Cyber Framework
    M Thiyagarajan, P.Nandakumar, R.Rajesh, P. Gopalsamy, Senthil Raja P, S.Kishore Verma
    7th International Conference on Energy Power and Environment Icepe 2025, 2025
  • MediBloom AI-Powered Public Health Assistant Revolutionizing Disease Awareness
    S. Usharani, P. Manju Bala, R. Rajesh, S. Ruddhra, V. Kiruthigaa, K. Rajkumar
    2025 4th International Conference on Smart Technologies and Systems for Next Generation Computing Icstsn 2025, 2025
  • An efficient self-attention-based conditional variational auto-encoder generative adversarial networks based multipath cross-layer design routing paradigm for MANET
    Kalaimani Shanmugham, Rajesh Rangan, Saravanan Dhatchnamurthy, Sumit Pundir
    Expert Systems with Applications, 2024
  • Possession of Alliance with Distinct Organization for Contingency Model
    R. Rajesh, K. Vishnupriyan
    2023 IEEE International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2023, 2023
  • TRANSFORMED DATA RELAYING METHOD FOR COVERAGE HOLE PRONE WIRELESS SENSOR NETWORK
    Rajesh R., Dr. Tamizhazhagan V.
    Indian Journal of Computer Science and Engineering, 2022
  • Women Safety Android Application with Hardware Device
    Roselin G Leema, R Rajesh, M Rajeswari, V Akshaya, D Saravanan, N Sangeetha
    2021 International Conference on System Computation Automation and Networking Icscan 2021, 2021
  • Retrieval of Data and Visualization in a Quick-Witted Mirror through Voice Control and Artificial Intelligence
    Sarah Catharin S., Ramkumar. M. O., Rajesh R.
    2020 International Conference on System Computation Automation and Networking Icscan 2020, 2020
  • An Intelligent Computer Vision for Children Affected with Cerebral Palsy
    G. Vengatesh, R. Rajesh, T. Naveenkumar
    2020 International Conference on System Computation Automation and Networking Icscan 2020, 2020
  • Intelligent fruit fly algorithm for maximization coverage problem in wireless sensor network
    Nivetha D., Rajesh R., M.O. Ramkumar
    2020 7th International Conference on Smart Structures and Systems Icsss 2020, 2020
  • Digitized exam paper evaluation
    R Rajesh., R Kanimozhi.
    2019 IEEE International Conference on System Computation Automation and Networking Icscan 2019, 2019
  • Evaluation of mechanical properties of B4C filled glass-epoxy composites
    International Journal of Chemtech Research, 2015

RECENT SCHOLAR PUBLICATIONS

  • Enhancing radiographic image interpretation: WARES-PRS model for knee bone tumour detection
    R Usuff, S Kothandapani, R Rangan, S Dhatchnamurthy
    Network: Computation in Neural Systems 36 (3), 1107-1137 , 2025
    2025
  • Coordinate memory deduplication and partition for improving cloud efficiency
    R Premalatha, R Rajesh
    AIP Conference Proceedings 3137 (1), 020018 , 2025
    2025
  • An efficient self-attention-based conditional variational auto-encoder generative adversarial networks based multipath cross-layer design routing paradigm for MANET
    K Shanmugham, R Rangan, S Dhatchnamurthy, S Pundir
    Expert Systems with Applications 238, 122097 , 2024
    2024
    Citations: 17
  • Possession of alliance with distinct Organization for contingency model
    R Rajesh, K Vishnupriyan
    2023 International Conference on Research Methodologies in Knowledge … , 2023
    2023
    Citations: 4
  • ABCF—Augmented Boundary Coverage Framework for Improving Wireless Sensor Network Performance
    R Rajesh, V Tamizhazhagan
    Telematique, 197-209 , 2022
    2022
  • CANOS: Connectivity-Aware Neighbor Orchestration Scheme for Handling Coverage Holes in Wireless Sensor Networks.
    R Rajesh, V Tamizhazhagan
    Journal of Algebraic Statistics 13 (2) , 2022
    2022
  • TRANSFORMED DATA RELAYING METHOD FOR COVERAGE HOLE PRONE WIRELESS SENSOR NETWORK
    V Rajesh, R., Tamizhazhagan
    Indian Journal of Computer Science and Engineering (IJCSE) 13 (Jan-Feb 2022 … , 2022
    2022
  • Reference-Dependent Node Placement Scheme for Reducing Coverage Hole Complexity in Wireless Sensor Networks
    V Rajesh, R., Tamizhazhagan
    Design Engineering 2021 (9), Design Engineering , 2021
    2021
  • Women Safety Android Application with Hardware Device
    RG Leema, R Rajesh, M Rajeswari, V Akshaya, D Saravanan, ...
    2021 International Conference on System, Computation, Automation and … , 2021
    2021
    Citations: 8
  • Survey on Coverage Hole Optimization in WSN.
    R Rajesh, V Tamizhazhagan
    Turkish Online Journal of Qualitative Inquiry 12 (5) , 2021
    2021
  • Low power device coordination in internet of things environment using analytic hierarchy process model
    R Rajesh, C Annadurai, K Nirmaladevi
    Concurrency and Computation: Practice and Experience 33 (7), 1-1 , 2021
    2021
    Citations: 6
  • Intelligent fruit fly algorithm for maximization coverage problem in wireless sensor network
    D Nivetha, R Rajesh, R MO
    2020 7th International Conference on Smart Structures and Systems (ICSSS), 1-6 , 2020
    2020
    Citations: 5
  • Retrieval of Data and Visualization in a Quick-Witted Mirror Through Voice Control and Artificial Intelligence
    S Catharin, R MO
    2020 International Conference on System, Computation, Automation and … , 2020
    2020
  • An intelligent computer vision for children affected with cerebral palsy
    G Vengatesh, R Rajesh, T Naveenkumar
    2020 International Conference on System, Computation, Automation and … , 2020
    2020
    Citations: 4
  • Performance enhancement of IPv6 low power wireless personal area networks (6LoWPAN) by Lamport’s algorithm
    R Rajesh, C Annadurai, K Nirmaladevi
    Cluster Computing 22 (Suppl 4), 7745-7750 , 2019
    2019
    Citations: 8
  • Digitized exam paper evaluation
    R Rajesh, R Kanimozhi
    2019 IEEE International Conference on System, Computation, Automation and … , 2019
    2019
    Citations: 13
  • Low power device synchronization protocol for IPv6 over low power wireless personal area networks (6LoWPAN) in Internet of Things (IoT)
    R Rajesh, C Annadurai, D Ramkumar, I Nelson, I Jayakaran Amalraj
    International Conference on Emerging Current Trends in Computing and Expert … , 2019
    2019
    Citations: 3
  • Design and fabrication of pulverising unit for maximum absorptivity of raw banana fiber
    S Sreekumar, A Murali, A Aravind Vasudevaru, A Rajendran, R Rajesh, ...
    IOP Conference Series: Materials Science and Engineering 377 (1), 012039 , 2018
    2018
    Citations: 2
  • SMART PADDY CROP DISEASE IDENTIFICATION AND MANAGEMENT USING DEEP CONVOLUTION NEURAL NETWORK AND SVM CLASSIFIER
    UP R.Rajmohan, 2 M.Pajany, 3 R.Rajesh, 4 D.Raghu Raman
    International Journal of Pure and Applied Mathematics 118 (Special Issue … , 2018
    2018
    Citations: 64
  • Intelligent Social Media Notification System for Discourse App
    DR Raman, R Rajesh, R Rajmohan, M Pajany
    Software Engineering 10 (2), 17-22 , 2018
    2018

MOST CITED SCHOLAR PUBLICATIONS

  • Plant disease detection and its solution using image classification
    G Saradhambal, R Dhivya, S Latha, R Rajesh
    International Journal of Pure and Applied Mathematics 119 (14), 879-884 , 2018
    2018
    Citations: 123
  • SMART PADDY CROP DISEASE IDENTIFICATION AND MANAGEMENT USING DEEP CONVOLUTION NEURAL NETWORK AND SVM CLASSIFIER
    UP R.Rajmohan, 2 M.Pajany, 3 R.Rajesh, 4 D.Raghu Raman
    International Journal of Pure and Applied Mathematics 118 (Special Issue … , 2018
    2018
    Citations: 64
  • An efficient self-attention-based conditional variational auto-encoder generative adversarial networks based multipath cross-layer design routing paradigm for MANET
    K Shanmugham, R Rangan, S Dhatchnamurthy, S Pundir
    Expert Systems with Applications 238, 122097 , 2024
    2024
    Citations: 17
  • Digitized exam paper evaluation
    R Rajesh, R Kanimozhi
    2019 IEEE International Conference on System, Computation, Automation and … , 2019
    2019
    Citations: 13
  • Women Safety Android Application with Hardware Device
    RG Leema, R Rajesh, M Rajeswari, V Akshaya, D Saravanan, ...
    2021 International Conference on System, Computation, Automation and … , 2021
    2021
    Citations: 8
  • Performance enhancement of IPv6 low power wireless personal area networks (6LoWPAN) by Lamport’s algorithm
    R Rajesh, C Annadurai, K Nirmaladevi
    Cluster Computing 22 (Suppl 4), 7745-7750 , 2019
    2019
    Citations: 8
  • Predicting rainfall and forecast weather sensitivity using data mining techniques
    R Aswini, D Kamali, S Jayalakshmi, R Rajesh
    Int J Pure Appl Math 119 (14), 843-847 , 2018
    2018
    Citations: 7
  • Low power device coordination in internet of things environment using analytic hierarchy process model
    R Rajesh, C Annadurai, K Nirmaladevi
    Concurrency and Computation: Practice and Experience 33 (7), 1-1 , 2021
    2021
    Citations: 6
  • Intelligent fruit fly algorithm for maximization coverage problem in wireless sensor network
    D Nivetha, R Rajesh, R MO
    2020 7th International Conference on Smart Structures and Systems (ICSSS), 1-6 , 2020
    2020
    Citations: 5
  • Possession of alliance with distinct Organization for contingency model
    R Rajesh, K Vishnupriyan
    2023 International Conference on Research Methodologies in Knowledge … , 2023
    2023
    Citations: 4
  • An intelligent computer vision for children affected with cerebral palsy
    G Vengatesh, R Rajesh, T Naveenkumar
    2020 International Conference on System, Computation, Automation and … , 2020
    2020
    Citations: 4
  • Low power device synchronization protocol for IPv6 over low power wireless personal area networks (6LoWPAN) in Internet of Things (IoT)
    R Rajesh, C Annadurai, D Ramkumar, I Nelson, I Jayakaran Amalraj
    International Conference on Emerging Current Trends in Computing and Expert … , 2019
    2019
    Citations: 3
  • Design and fabrication of pulverising unit for maximum absorptivity of raw banana fiber
    S Sreekumar, A Murali, A Aravind Vasudevaru, A Rajendran, R Rajesh, ...
    IOP Conference Series: Materials Science and Engineering 377 (1), 012039 , 2018
    2018
    Citations: 2
  • Enhancing radiographic image interpretation: WARES-PRS model for knee bone tumour detection
    R Usuff, S Kothandapani, R Rangan, S Dhatchnamurthy
    Network: Computation in Neural Systems 36 (3), 1107-1137 , 2025
    2025
  • Coordinate memory deduplication and partition for improving cloud efficiency
    R Premalatha, R Rajesh
    AIP Conference Proceedings 3137 (1), 020018 , 2025
    2025
  • ABCF—Augmented Boundary Coverage Framework for Improving Wireless Sensor Network Performance
    R Rajesh, V Tamizhazhagan
    Telematique, 197-209 , 2022
    2022
  • CANOS: Connectivity-Aware Neighbor Orchestration Scheme for Handling Coverage Holes in Wireless Sensor Networks.
    R Rajesh, V Tamizhazhagan
    Journal of Algebraic Statistics 13 (2) , 2022
    2022
  • TRANSFORMED DATA RELAYING METHOD FOR COVERAGE HOLE PRONE WIRELESS SENSOR NETWORK
    V Rajesh, R., Tamizhazhagan
    Indian Journal of Computer Science and Engineering (IJCSE) 13 (Jan-Feb 2022 … , 2022
    2022
  • Reference-Dependent Node Placement Scheme for Reducing Coverage Hole Complexity in Wireless Sensor Networks
    V Rajesh, R., Tamizhazhagan
    Design Engineering 2021 (9), Design Engineering , 2021
    2021
  • Survey on Coverage Hole Optimization in WSN.
    R Rajesh, V Tamizhazhagan
    Turkish Online Journal of Qualitative Inquiry 12 (5) , 2021
    2021

GRANT DETAILS

Received two seminar grants from ISRO(Indian Space Research Organisation)
1. Internet of things for “Effective Disaster Management”
Sanction number-
2. Internet of things-Early warning System
Sanction number-
Received one Conference grant from DHR(Department of Health and Research.
1. Deep Learning Applications-Medical field(Dec 2018)
Sanction number- File