D. Balakrishnan

Kalasalingam Academy of Research and Education

Papers

Total Citations

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About

D. Balakrishnan is making impactful strides at the intersection of computer vision and intelligent transportation systems, with a particular focus on real-time object detection. Their most-cited work, "Object Detection on Traffic Data Using YOLO" (2023, 4 citations), demonstrates a practical application of deep learning to one of the most pressing challenges in autonomous driving and smart city infrastructure. By leveraging the YOLO (You Only Look Once) architecture, Balakrishnan has contributed to making traffic scene analysis faster and more efficient, enabling vehicles and surveillance systems to identify pedestrians, vehicles, and obstacles with greater accuracy. This research is foundational for developing safer, more responsive autonomous navigation systems. While early in their citation trajectory, the work’s relevance to the rapidly growing fields of edge AI and real-time video analytics signals strong potential for future impact. Balakrishnan’s contributions are particularly valuable for researchers and engineers seeking to bridge the gap between state-of-the-art object detection algorithms and their deployment in resource-constrained, real-world environments like traffic monitoring.