Nasser Kehtarnavaz

The University of Texas at Dallas, Texas A&M University

Papers

Total Citations

168

H-Index

About

Nasser Kehtarnavaz is a leading figure in computer vision and image processing, with a career spanning autonomous navigation to deep learning. His foundational work on collision-free navigation for autonomous vehicles, as seen in his 2003 paper (19 citations), established early frameworks for handling moving obstacles with unknown trajectories—a critical challenge in robotics. However, his most impactful contribution lies in the domain of image segmentation. His 2021 survey, "Image Segmentation Using Deep Learning: A Survey," has garnered 143 citations, reflecting its role as a definitive resource for researchers and practitioners. This work systematically reviews deep learning architectures for scene understanding, medical imaging, and video surveillance, bridging classical methods with modern AI. Kehtarnavaz also contributed to stereo vision systems, analyzing camera movement errors in vehicle tracking (1995). His research demonstrates a sustained commitment to solving real-world problems, from autonomous vehicle safety to advanced image analysis. With over 140 citations on his top paper alone, Kehtarnavaz’s work continues to guide students and engineers navigating the intersection of robotics, computer vision, and deep learning.