Dr.SAMPATH RAJARAM
Sri Sairam Institute of Technology, SRM Institute of Science and Technology
0000-0001-9806-3912
About
Dr.R.Sampath completed his undergraduate program in information technology from MaduraiKamaraj University. He completed his postgraduate program from SRM Institute of Science andTechnology and also completed his PhD at SRM Institute of Science and Technology Chennaiand working as Associate Professor in the Department of Information Technology at Sri Sai RamInstitute of Technology, Chennai. He is a senior member IEEE and also members of various societies. He has published more than 25 International Journals Indexed in SCI and Scopus His area of interests includes Machine Learning, Deep Learning, image processing, artificial neuralnetworks, Medical image processing and data mining, Alzheimer’s disease prediction, bodysensor networks, and disease prediction systems.
Employment
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Sri Sairam Institute of Technology Associate Profesor
Education
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SRM Institute of Science and Technology Ph D2021 - 2024
Projects & Funding
Projects & funding information is unavailable.
Publications (21)
- DTLN: Deep Transformer Learning Network for Multi-Wavelength Strain Classification in Sports Wearables Save
- A fine-grained data analytical model for electronic healthcare data error mitigation Save
- A comprehensive cross-attention and fuzzy segmentation approach for rice plant disease detection Save
- Adaptive Neuro-Fuzzy Inference System (ANFIS) for Clinical Decision Support in Remote Patient Monitoring Save
- Biomarker extraction-based Alzheimer's disease stage detection using optimized deep learning approach Save
- Semantic Image Retrieval Using CNN-Based Feature Hashing and Density-Based Clustering Techniques Save
- Alzheimer’s Disease Prediction Using Fly-Optimized Densely Connected Convolution Neural Networks Based on MRI Images Save
- An Optimized Deep Learning Approach To Identfiy the Alzheimer's Stages Identification Based on Biomarkers Extraction Save
- Automated Feedback System Save
- Whale Optimized Deep Generative Adversarial Network Based Alzheimer's Stages Detection Using 3D MRI Brain Neuroimaging Save