A Generalized Deep Learning Approach for Cross-Crop Plant Disease Detection Using the Plant Village Dataset Roopa R, Rajesh Lingam, Santosh Kumar Ravva, Suresh A, Penubaka Balaji, et al. Journal of Machine and Computing, 2025 Plant diseases continue to be one of the leading causes of reduced agricultural productivity worldwide, directly threatening food supply chains and the economic stability of farming communities. With the global population steadily increasing, the demand for intelligent, scalable, and highly accurate plant disease detection systems has never been more critical. Deep learning methods have shown promising results in this field; however, numerous conventional models cannot often generalize well across different crop species and unseen disease types. These limitations hinder their practical deployment in dynamic real-world agricultural environments. In this study, we propose a robust and generalized deep learning-based approach for cross-crop plant disease detection, using the comprehensive and diverse Plant Village dataset. Our model is built upon a custom-designed Convolutional Neural Network (CNN) architecture that incorporates a small Inception module. Unlike traditional CNNs, which primarily focus on the global features of a leaf. Our model detects and analyzes localized disease spread patterns, enhancing detection across diverse crops and adapting to novel conditions. The small Inception module plays a vital role in enabling multi-scale feature extraction from small disease-affected patches without adding excessive computational complexity. This architectural refinement allows the model to learn more discriminative features, resulting in faster convergence and higher classification accuracy. When trained and validated on the Plant Village dataset, our model achieved an impressive accuracy of 98.45%, outperforming many traditional approaches. Additionally, it demonstrated consistently high precision, recall, and F1-score, confirming its reliability and robustness. By addressing the challenges of overfitting and poor generalization, common pitfalls in many deep learning models, our method provides a scalable and effective solution for real-time agricultural disease monitoring. This work contributes to the growing field of precision agriculture by offering a model that is not only accurate but also generally efficient and practical for deployment in diverse agricultural settings. Ultimately, our research aims to support the development of smart farming technologies that ensure healthier crops and contribute to long-term global food security.
Efficient and Accurate Traffic Sign Detection Leveraging YOLOv8: A Cutting-Edge Deep Learning Framework Gunji Sreenivasulu, Lakshmi H N, Muni Kumari T, Anjaiah P, Suresh A, et al. Journal of Machine and Computing, 2025 The timely and precise identification of traffic signs is essential for maintaining the effectiveness and safety of contemporary roads, particularly in light of the increasing number of self-driving cars. Conventional image processing methods have faced challenges because to the intricate and fluctuating variables present in real-world settings, including various signage, erratic weather, and inconsistent illumination. This study utilizes recent breakthroughs in deep learning, particularly the YOLOv8 (You Only Look Once version 8) model, to tackle these difficulties. YOLOv8 incorporates cutting-edge neural network architectural advancements, such as an anchor-free detection methodology, adaptive spatial feature pooling, and dynamic neural configurations. In order to further increase detection efficiency and accuracy, this study presents two innovative models, YOLOv8-DH and YOLOv8-TDHSA. These models make use of improvements such decoupled heads and transformer-based self-attention mechanisms. Experimental results indicate that the suggested models substantially surpass current deep learning models, attaining enhanced performance across multiple measures, including accuracy, recall, F-score, and mean average precision (mAP). This research enhances traffic sign detecting technology, facilitating the development of safer and more intelligent transportation systems.
Brain Stroke Prognosis: A Fusion of Machine Learning and Deep Learning A. Suresh, V Sambasiva, P. Somya, G. Yashmitha, K. Soma Sagar, et al. 2025 International Conference on Data Science and Business Systems Icdsbs 2025, 2025 Since brain stroke is one of the world's major causes of disability and death, accurate prediction models are essential for prompt diagnosis and treatment. The research analyzes combined approaches between machine learning (ML), deep learning (DL), and ensemble-based techniques for improving brain stroke outcome prediction. The research utilized a dataset containing demographics alongside lifestyle factors and medical information processed through normalization and imputation as well as the Synthetic Minority Oversampling Technique (SMOTE) which addressed class imbalance issues and solved missing values. The research examines four popular modeling approaches starting with Support Vector Machines (SVM) and Random Forest (RF) followed by CatBoost then Convolutional Neural Networks (CNN) and an improved ensemble combination. The ensemble model performed exceptionally well across comprehensive performance metrics which demonstrated accuracy at 96 % and precision at 97 % with recall at 96 %. Support Vector Machines showed outstanding recall performance which makes the model an ideal choice for medical applications that need successful diagnosis detection. The author stresses how ensemble approaches use different models to generate precise predictions for stroke outcomes. Advanced predictive systems in healthcare receive implementation guidance through these findings that will lead to enhanced patient results in critical medical conditions.
ML Based Framework for Predicting Red Wine Quality A. Suresh, M. Giri, K. Ammulu, N. Babu, B. Anandan, et al. 2025 17th IEEE International Conference on Computational Intelligence and Communication Networks Cicn 2025, 2025
Advanced Cardiovascular Disease Prediction: A Comparative Analysis of Ensemble Stacking and Deep Neural Networks International Journal of Intelligent Systems and Applications in Engineering, 2024
Cloud Computing’s Effect on Video Games Streaming A. Komathi, J. Lenin, S. Asha, A. Suresh, M. Suguna, et al. 2nd International Conference on Automation Computing and Renewable Systems Icacrs 2023 Proceedings, 2023
Enhancing layout design in aluminum die casting for reduced cycle time and material handling distance A Suresh, A Ramesh Mechanics of Advanced Materials and Structures 33 (1), 2669359 , 2026 2026
Federated hyper LSTM model for storage optimization and collision prediction in an intelligent IoVT A Balajee, R Vinoth, A Suresh, M Khan, TR Mahesh, A Sayal Egyptian Informatics Journal 33, 100884 , 2026 2026
Experimental Study on Mechanical, Thermal Conductivity, Wear, and Water Absorption Behaviour of Calotropis gigantea Stem Fiber/Citrus Maxima ZnO Reinforced Epoxy Composites A Suresh, L Jayakumar Silicon, 1-16 , 2026 2026
Tesla Coil-Powered Wireless Charging for Drone in Supply Chain Optimization A Suresh, G Pranesh, ST Anbu, R Sankarasubramani, K Nagarjun ADVANCES IN ADDITIVE MANUFACTURING TECHNOLOGIES, 373-378 , 2026 2026
Adaptive Multi-Path Energy Optimization in WSN Using Machine Learning and Meta heuristic Techniques M Giri, A Suresh, N Babu, KA Kumar, B Anandan, MS Rao 2025 IEEE 17th International Conference on Computational Intelligence and … , 2025 2025
ML Based Framework for Predicting Red Wine Quality A Suresh, M Giri, K Ammulu, N Babu, B Anandan, MS Rao 2025 IEEE 17th International Conference on Computational Intelligence and … , 2025 2025
Non-Invasive Sensor-Based Health Monitoring and Prediction in an Iot Environment A Suresh, M Giri, MMMK Varma, N Babu, B Anandan, MS Rao 2025 IEEE 17th International Conference on Computational Intelligence and … , 2025 2025 Citations: 1
A Predictive Model for Cardio Stroke Risk Using Hybrid Machine Learning N Babu, M Giri, A Suresh, MLM Prasad, B Anandan, MS Rao 2025 IEEE 17th International Conference on Computational Intelligence and … , 2025 2025
Predictor: Critical Illness from Chronic Problems and Discovered Features using ML M Giri, A Suresh, N Babu, B Anandan, S Vanathi, N Kamal 2025 5th International Conference on Internet of Things: Smart Innovation … , 2025 2025
Leveraging Multi-modal Datasets to Enhance Diagnostic Accuracy and Reliability in MRI Images for Brain Tumor Classification D Ramya Dorai, R Vinoth, A Suresh, TR Mahesh Biomedical Materials & Devices, 1-16 , 2025 2025
Advancing Corporate Finance: A Multigranularity Approach to Bankruptcy Prediction A Suresh, K Durairaj, B Anandan, KDM Sundaram, BR Babu 2025 IEEE International Conference on Advanced Computing Technologies (ICACT … , 2025 2025
Self-Attention Recurrent Reinforcement Learning Based Anomaly Detection for Dynamic Spectrum Access in Cognitive Radio Networks Sachinkumar, A Suresh, R Patil, A Sreedevi, Y Chanti International Conference on 6G Communications Networking and Signal … , 2025 2025
Fine-Tuned K-Nearest Neighbor for Hybrid Beamforming Algorithm in Massive MIMO Systems J Lande, A Suresh, KS Shashidhara, A Sreedevi, TS Ghouse Basha International Conference on 6G Communications Networking and Signal … , 2025 2025
Manufacturing of Wind Turbine Blades Using PLA and ABS Materials S Rajakumar, A Suresh, VS Greeshma Recent Developments in Wind Engineering: Select Proceedings of NCWE 2024, 361 , 2025 2025
Empowering Fake News Detection Through Innovative Hybrid Deep Learning-Based Approach A Suresh, RM Mallika, S Gireesh, GHK Singh, ES Jeevanandham, ... 2025 International Conference on Computing for Sustainability and … , 2025 2025
A novel approach for predicting net irrigated area in India using hybrid deep learning architectures NV Palanichamy, M Kalpana, N Balakrishnan, A Suresh, V Balamurugan, ... 2025
IoT-Enabled Smart Parking System using Machine Learning for Real-Time Parking Prediction A Suresh, P Chandu, SSC Bose, V Dhamini, PA Narayana, KD Balaji 2024 4th International Conference on Mobile Networks and Wireless … , 2024 2024 Citations: 2
Topology Optimization of Electric Solar Vehicle Brake Pedal S Pavithra, A Suresh, RG Moorthy, A Parthiban, D Dinesh, ... Advances in Additive Manufacturing Technologies, 414-417 , 2024 2024
LM6 Aluminium Alloy Processing by Die Casting—A State of the Art A Parthiban, A Ramesh, A Suresh, D Dinesh, PS Kanishkha Advances in Additive Manufacturing Technologies, 326-330 , 2024 2024
Design and Analysis of a Rugged Swing-Arm for Electric Two-Wheelers K Swamy, A Suresh, S Ravi, K Niranjan, R Srivardhan, SM Nishanth Advances in Additive Manufacturing Technologies, 145-149 , 2024 2024
MOST CITED SCHOLAR PUBLICATIONS
Changes in protein metabolism in hemolymph and fat body of the silkworm, Bombyx mori (Lepidoptera: Bombycidae) in response to organophosphorus insecticides toxicity BS Nath, A Suresh, BM Varma, RPS Kumar Ecotoxicology and environmental safety 36 (2), 169-173 , 1997 1997 Citations: 152
Design of small horizontal axis wind turbine for low wind speed rural applications A Suresh, S Rajakumar Materials Today: Proceedings 23, 16-22 , 2020 2020 Citations: 99
Comparative study on the inhibition of acetylcholinesterase activity in the freshwater fish Cyprinus carpio by mercury and zinc. A Suresh, B Sivaramakrishna, PC Victoriamma, K Radhakrishnaiah Biochemistry international 26 (2), 367-375 , 1992 1992 Citations: 84
Bioaccumulation of nickel in the organs of the freshwater fish, Cyprinus carpio, and the freshwater mussel, Lamellidens marginalis, under lethal and sublethal nickel stress P Sreedevi, A Suresh, B Sivaramakrishna, B Prabhavathi, ... Chemosphere 24 (1), 29-36 , 1992 1992 Citations: 78
Microalgal fatty acid methyl ester a new source of bioactive compounds with antimicrobial activity A Suresh, R Praveenkumar, R Thangaraj, FL Oscar, E Baldev, ... Asian Pacific Journal of Tropical Disease 4, S979-S984 , 2014 2014 Citations: 76
Bright, low voltage europium doped gallium oxide thin film electroluminescent devices P Wellenius, A Suresh, JF Muth Applied Physics Letters 92 (2) , 2008 2008 Citations: 74
Effect of nickel on some aspects of protein metabolism in the gill and kidney of the freshwater fish, Cyprinus carpio L. P Sreedevi, B Sivaramakrishna, A Suresh, K Radhakrishnaiah Environmental Pollution 77 (1), 59-63 , 1992 1992 Citations: 72
Patterns of cadmium accumulation in the organs of fry and fingerlings of freshwater fish Cyprinuscarpio following cadmium exposure A Suresh, B Sivaramakrishna, K Radhakrishnaiah Chemosphere 26 (5), 945-953 , 1993 1993 Citations: 71
A visible transparent electroluminescent europium doped gallium oxide device P Wellenius, A Suresh, JV Foreman, HO Everitt, JF Muth Materials Science and Engineering: B 146 (1-3), 252-255 , 2008 2008 Citations: 69
Changes in protein metabolism in haemolymph and fat body of the silkworm, Bombyx mori L., in response to organophosphorus insecticides toxicity BS Nath, A Suresh, B Mahendra Varma, RP Kumar Ecotoxicol. Environ. Saf 36, 169-173 , 1997 1997 Citations: 62
Cloud Computing’s Effect on Video Games Streaming A Komathi, J Lenin, S Asha, A Suresh, M Suguna, C Srinivasan 2023 2nd International Conference on Automation, Computing and Renewable … , 2023 2023 Citations: 56
Biodiversity of microalgae in Western and Eastern Ghats, India. A Suresh, RP Kumar, D Dhanasekaran, N Thajuddin Pakistan Journal of Biological Sciences: PJBS 15 (19), 919-928 , 2012 2012 Citations: 41
Evaluation and characterization of the plant growth promoting potentials of two heterocystous cyanobacteria for improving food grains growth A Suresh, S Soundararajan, S Elavarasi, FL Oscar, N Thajuddin Biocatalysis and Agricultural Biotechnology 17, 647-652 , 2019 2019 Citations: 38
Investigation of mechanical and wear characteristic of Banana/Jute fiber composite A Suresh, L Jayakumar, A Devaraju Materials Today: Proceedings 39, 324-330 , 2021 2021 Citations: 37
Glutathione-S-transferase and catalase activity in different tissues of marine catfish Arius arius on exposure to cadmium R Mani, B Meena, K Valivittan, A Suresh International Journal of Pharmacy and Pharmaceutical Sciences 6 (1), 326-332 , 2014 2014 Citations: 35
Cadmium induced changes in ion levels and ATPase activities in the muscle of the fry and fingerlings of the freshwater fish, Cyprinus carpio A Suresh, B Sivaramakrishna, K Radhakrishnaiah Chemosphere 30 (2), 367-375 , 1995 1995 Citations: 35
Effects of lethal and sublethal concentrations of copper on glycolysis in liver and muscle of the freshwater teleost, Labeo rohita(Hamilton). K Radhakrishnaiah, P Venkataramana, A Suresh, B Sivaramakrishna Journal of Environmental Biology 13 (1), 63-68 , 1992 1992 Citations: 33
Flexural behaviour of reinforced geopolymer concrete incorporated with hazardous heavy metal waste ash and glass powder AS Kumar, M Muthukannan, A Irene, KK Arun, AC Ganesh Materials science forum 1048, 345-358 , 2022 2022 Citations: 32
Effect of lethal and sublethal concentrations of Cadmium on energetics in the gills of fry and fingerlings of Cyprinus carpio A Suresh, B Sivaramakrishna, K Radhakrishnaiah Bulletin of environmental contamination and toxicology 51 (6), 920-926 , 1993 1993 Citations: 32
Effect of sublethal concentration of mercury and zinc on the energetics of a freshwater fish Cyprinus carpio (Linnaeus). K Radhakrishnaiah, A Suresh, B Sivaramakrishna Acta Biologica Hungarica 44 (4), 375-385 , 1993 1993 Citations: 31