A. V. Narasimhadhan

Sardar Vallabhbhai National Institute of Technology Surat, National Institute of Technology Karnataka

Papers

Total Citations

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About

A. V. Narasimhadhan is a researcher specializing in computer vision, deep learning, and autonomous systems, with a particular focus on intelligent transportation and visual perception technologies. His most recognized contribution is a novel lane detection framework leveraging Convolutional Neural Networks (CNNs) built upon the SegNet encoder-decoder architecture, which utilizes Google Street View data to enable robust, real-world autonomous navigation. This work, which has garnered 22 citations, addresses a critical challenge in the development of fully assistive and self-driving vehicle systems, demonstrating both practical ingenuity and technical depth. Narasimhadhan has also contributed to the broader field of object tracking through a comparative analysis of illumination invariant techniques, tackling persistent challenges in video surveillance and human-computer interaction such as lighting variation and pose estimation. His research reflects a consistent commitment to solving real-world computer vision problems, bridging the gap between theoretical models and applied autonomous systems. Though still an emerging voice in the field, his work provides meaningful groundwork for researchers advancing robust perception systems in dynamic, uncontrolled environments.