Sadaf Yasmin
Papers
2
Total Citations
62
H-Index
2
About
Sadaf Yasmin is a leading researcher in computer vision and artificial intelligence, with a primary focus on spatiotemporal human action recognition and autonomous vehicle safety. Her most cited work, "A transfer learning-based efficient spatiotemporal human action recognition framework for long and overlapping action classes" (2021, 48 citations), introduces a novel deep learning framework that addresses the critical challenge of accurately classifying complex, overlapping human actions in video sequences. This contribution has significant implications for surveillance, human-computer interaction, and sports analytics. Dr. Yasmin has also made impactful strides in autonomous driving safety through her 2022 paper on small obstacle detection on roads using semantic segmentation (14 citations). This work tackles the pressing issue of identifying small, hazardous objects on highways—a major cause of severe incidents—thereby enhancing the reliability of autonomous vehicle navigation systems. Her research demonstrates a powerful blend of theoretical innovation and practical application, earning her recognition as a rising authority in intelligent systems and safety-critical AI.
Research Focus
Key Achievements
Top Papers
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