Rama Sai Mamidala

National Institute of Technology Karnataka

Papers

Total Citations

H-Index

About

Rama Sai Mamidala is a researcher in autonomous vehicle technology, with a primary focus on computer vision and deep learning for intelligent transportation systems. His most significant contribution lies in lane detection—a critical component for fully-assistive and autonomous navigation. In his highly cited 2019 work, Mamidala introduced a novel and pragmatic approach that leverages a convolutional neural network (CNN) based on the SegNet encoder-decoder architecture, combined with Google Street View imagery. This dynamic method demonstrates a practical, data-driven solution for real-world lane detection challenges, offering a robust alternative to traditional algorithms. With over 28 combined citations for his foundational paper, Mamidala’s work has provided a valuable benchmark for researchers developing advanced driver-assistance systems (ADAS). His research directly addresses the need for reliable, scalable perception systems in autonomous vehicles, showcasing his ability to bridge theoretical deep learning models with applied engineering problems. Mamidala’s contributions continue to influence the evolution of safer, more efficient autonomous navigation technologies.