T. Keerthi

Papers

Total Citations

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About

T. Keerthi is an emerging researcher in the fields of embedded systems, computer vision, and autonomous driving technologies. Their work focuses on developing practical, hardware-accelerated solutions for real-world robotics and vehicular applications. Keerthi’s most notable contribution is a novel method for door detection on FPGAs using the Sobel edge algorithm, designed to create assistive devices for the elderly and physically disabled. This work, published in 2022, has garnered 4 citations for its innovative approach to real-time, low-power obstacle recognition. In 2023, Keerthi advanced autonomous driving research by proposing an automatic vehicle speed control system based on traffic sign recognition using convolutional neural networks (CNNs). This study addresses the critical challenge of enabling autonomous systems to interpret and react to traffic signs accurately, contributing to safer self-driving technologies. While early in their career, Keerthi’s research demonstrates a clear commitment to bridging hardware efficiency with intelligent algorithms, making their work relevant for students and engineers interested in FPGA-based edge computing, assistive robotics, and the practical deployment of deep learning in autonomous vehicles.