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S.Raguvaran
S.Raguvaran
Assistant Professor, Department of Computational Intelligence, School of Computing, SRM University
在 srmist.edu.in 的电子邮件经过验证
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引用次数
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Recognition of animal species on camera trap images using machine learning and deep learning models
R Thangarasu, VK Kaliappan, R Surendran, K Sellamuthu, J Palanisamy
Int. J. Sci. Technol. Res 10, 2-11, 2019
142019
Twitter sentiment analysis using conditional generative adversarial network
V Mahalakshmi, P Shenbagavalli, S Raguvaran, V Rajakumareswaran, ...
International Journal of Cognitive Computing in Engineering 5, 161-169, 2024
92024
DeepFake detection using transfer learning-based Xception model
V Rajakumareswaran, S Raguvaran, V Chandrasekar, S Rajkumar, ...
Advanced Information Systems 8 (2), 89-98, 2024
32024
Heart Disease Prediction Using Hybrid Machine Learning Algorithms, Vol. 13 No. 01 (2020): Vol 13 No 1 (2020)
S Raguvaran, R Anandhi, A Anbarasi, T Megala
2
AI-Powered Healthcare System to Fight the COVID-19 Pandemic on Federated Learning
S Gnanamurthy, S Raguvaran, BS Kumar, CS Kumar, MS Hemawathi
Federated Learning and AI for Healthcare 5.0, 178-202, 2024
12024
Harnessing LSTM Classifier to Suggest Nutrition Diet for Cancer Patients.
S Raguvaran, S Anandamurugan, AMJ Zubair Rahman
Intelligent Automation & Soft Computing 35 (2), 2023
12023
Enhancement of energy utilization efficiency and speed control of autonomous electric vehicles (AEVs): A hybrid approach
S Raguvaran, S Anandamurugan
Energy Efficiency 17 (6), 59, 2024
2024
From Industry 4.0 to 5.0: Digital Management Model of Personnel Archives Based on Transition From Digital Manufacturing
P Sakthivel Velusamy, S. Raguvaran
Emerging Technologies in Digital Manufacturing and Smart Factories 1, pages 1-25, 2024
2024
Heavy Duty Vehicle Trap Using Mask Rcnn Algorithm
MS Raguvaran, SS Shabanabanu
Annals of the Romanian Society for Cell Biology, 4225-4240, 2021
2021
Recommendation of food tourism using Artificial Neural Network–A survey
P Suruthi, S Raguvaran
2019
Integrated Forest Fire Detection System for Identifying Living Beings using Drones by Employing Custom TrainedYOLOv5 Model
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