Phanindra Tallapragda
Papers
1
Total Citations
7
H-Index
1
About
Phanindra Tallapragda is a researcher at the forefront of integrating artificial intelligence with autonomous vehicle control systems. His primary research areas include deep learning, computer vision, and trajectory tracking for autonomous navigation. Tallapragda’s most notable contribution is his pioneering work on the virtual evaluation of deep learning techniques for vision-based trajectory tracking, published in 2022. This paper has already garnered 7 citations, demonstrating its early impact in the field. His research addresses the critical challenge of replacing traditional control systems with AI-enhanced alternatives, offering a more adaptable and scalable approach to vehicle guidance. By developing and validating deep learning models in simulated environments, Tallapragda provides a framework for safer and more efficient autonomous driving systems. His work is particularly significant for students and researchers exploring the intersection of artificial intelligence and robotics, as it bridges the gap between theoretical deep learning methods and practical control applications. Tallapragda’s contributions are helping to shape the next generation of intelligent transportation systems.
Research Focus
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Top Papers
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