suganthi
Vellore Institute of Technology chennai, VIT University - Chennai Campus, Anna University Chennai, Madras Institute of Technology, Bannari Amman Institute of Technology
0000-0003-4064-6394
About
Dr. K. Suganthi received the B.E. degree in Computer Science and Engineering from Madras University in 2001, M.Tech degree in Systems Engineering and Operations Research and Ph.D in Wireless Sensor Network from the Anna University in 2006 and 2016 respectively. She is currently working as Associate Professor in the School of Electronics Engineering. She is the author of about 50 scientific publications on journals and International conferences. Her research interests include Deep learning,Wireless Sensor Network, Internet of Things, Data Analytics and Medical image analysis.
Google scholar profile: https://scholar.google.co.in/citations?hl=en&user=QVypuzIAAAAJ
Future work:
• Applying Deep Learning algorithms to solve wireless sensor network/IoT challenges
• Detection of knee ligament tear from MRI and CT images
• Developing a tool to support disabled and elderly persons using latest technologies.
Employment
-
Vellore Institute of Technology chennai Associate Professor2022 - Present
-
VIT University - Chennai Campus Assistant professor (Senior)2016 - Present
-
Bannari Amman Institute of Technology Assistant professor2015 - 2016
-
Madras Institute of Technology Teaching fellow2007 - 2015
Education
-
Anna University Chennai Phd2010 - 2016
-
Madras Institute of Technology ME2003 - 2006
Projects & Funding
Projects & funding information is unavailable.
Publications (62)
- Lightweight Hybrid Foreign Object Detection Framework with Scene Aware and Uncertainty Fusion Mechanism Save
- Lightweight hybrid foreign object detection framework with scene aware and uncertainty fusion mechanism Save
- Explainable AI for the diagnosis of neurodegenerative diseases: Unveiling methods, opportunities, and challenges Save
- A CNN–Transformer Fusion Approach Integrating Texture Encoding and Cross-Patch Attention for Efficient Histopathological Breast Cancer Classification Save
- Oil spill segmentation of noisy SAR images using domain adaptation based UNet Save
- A quantum–classical dual-track deep learning network for explainable Parkinson’s disease classification Save
- An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network Save
- An Explainable Deep Learning Network With Transformer and Custom CNN for Bean Leaf Disease Classification Save
- Advanced Multi-Scale Enhanced U-Net for Efficient Land Cover Classification of Remote Sensing Images Save
- A Convolutional Mixer-Based Deep Learning Network for Alzheimer’s Disease Classification from Structural Magnetic Resonance Imaging Save