Muhammad Usman Karim Khan
Papers
2
Total Citations
11
H-Index
2
About
Muhammad Usman Karim Khan is a researcher specializing in computer vision and embedded systems, with a particular focus on memory-efficient algorithms for resource-constrained platforms. His work addresses the critical challenge of enabling sophisticated visual processing on tiny mobile robots and systems with limited fast memory. Khan’s most notable contribution is the development of a swift and memory-efficient Hough transform, detailed in his 2009 paper (9 citations), which optimizes line feature extraction for real-time applications in compact hardware. This approach significantly reduces memory footprint while maintaining performance, making advanced vision tasks feasible for small-scale robotics. His subsequent work on memory-efficient vision-based line feature extraction (2 citations) further demonstrates his commitment to practical, low-power solutions for autonomous navigation. By bridging the gap between theoretical computer vision and the stringent constraints of embedded systems, Khan has laid foundational work for efficient visual perception in mobile robotics, enabling smarter, more autonomous devices in environments where computational resources are at a premium.
Research Focus
Key Achievements
Top Papers
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