R. Jebi Nalatharaj

Kalasalingam Academy of Research and Education

Papers

Total Citations

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About

R. Jebi Nalatharaj is a researcher whose work sits at the intersection of computer vision and intelligent transportation systems, with a particular focus on real-time object detection. Their most cited paper, "Object Detection on Traffic Data Using Yolo" (2023), has garnered 4 citations and demonstrates a practical application of deep learning to traffic monitoring. This work explores how YOLO (You Only Look Once) algorithms can be adapted for the challenging task of identifying and localizing vehicles, pedestrians, and other objects in dynamic traffic scenes. By focusing on real-time performance and accuracy, Nalatharaj’s research contributes to the development of smarter, safer transportation infrastructure. Their work is particularly relevant for autonomous driving, traffic management, and surveillance systems. While still early in their career, Nalatharaj has established a foundation in applied computer vision, showing promise for future contributions to the field. Their research addresses a critical need for efficient, scalable object detection in real-world environments, making it a valuable resource for students and researchers working on intelligent transportation and AI-driven monitoring systems.