C. Senthilkumar

Papers

Total Citations

101

H-Index

About

C. Senthilkumar’s research lies at the intersection of computer vision, deep learning, and autonomous robotic systems, with a particular focus on solving real-world sensing and automation challenges. His most cited work, “An Effectual Underwater Image Enhancement using Deep Learning Algorithm” (2021, 60 citations), addresses a critical bottleneck in marine robotics and underwater network formation by developing novel deep learning techniques to restore clarity to degraded underwater imagery. This contribution is vital for applications ranging from environmental monitoring to autonomous underwater vehicle navigation. In parallel, his influential paper “Mobile robot for retail inventory using RFID” (2016, 41 citations) demonstrates a practical, high-impact innovation: an autonomous robot that leverages RFID technology to perform retail inventory, theft detection, and automated checkout with unprecedented efficiency. By bridging advanced image processing with tangible robotic deployment, Senthilkumar’s work has directly shaped both the theoretical foundations and applied methodologies in underwater vision enhancement and smart retail automation. His research continues to inspire new approaches in deep learning-based image restoration and intelligent robotic perception systems.