Muhammad Usman Ghani Khan
Papers
3
Total Citations
49
H-Index
3
About
Muhammad Usman Ghani Khan is a leading researcher in computer vision and autonomous robotics, with a focus on advancing multi-object tracking and motion prediction. His most cited work, "STMMOT: Advancing multi-object tracking through spatiotemporal memory networks and multi-scale attention pyramids" (2023, 28 citations), introduces a novel framework that leverages spatiotemporal memory and multi-scale attention to significantly improve tracking accuracy in complex video scenes. This contribution addresses critical challenges in real-world applications like surveillance and autonomous driving. Khan also explores predictive modeling in "Predicting humans future motion trajectories in video streams using generative adversarial network" (2021, 17 citations), using GANs to forecast human movement, enhancing safety in human-robot interaction. In robotics, his work on "ROS-Based Global Path Planning for Autonomous Ground Robot Using the Pre-Built Map of the Environment" (2021) tackles optimal pathway planning, preventing robots from getting stuck in local minima—a fundamental issue in autonomous navigation. With a growing citation record, Khan’s interdisciplinary research bridges perception and planning, making impactful strides toward more intelligent, autonomous systems.
Research Focus
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Top Papers
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