Muhammad Ihsan
Papers
1
Total Citations
1
H-Index
1
About
Muhammad Ihsan is a leading researcher at the intersection of edge artificial intelligence, mobile deep learning, and search-and-rescue (SAR) robotics. His work focuses on developing lightweight, real-time video analytics frameworks that enable autonomous robots to perform critical victim detection in post-disaster environments. Ihsan’s most-cited contribution, "Edge AI-Driven Video Analytics: A Mobile Deep Learning Framework for Victim Detection in SAR Robotics" (2024), addresses a fundamental challenge in SAR missions: distinguishing actual victims from visually similar dummy objects. By optimizing deep learning models for deployment on resource-constrained robotic platforms, his framework achieves high detection accuracy without sacrificing inference speed—a crucial trade-off for time-sensitive operations. This work has already garnered early citations, signaling its growing influence in the fields of edge computing and disaster robotics. Ihsan’s research not only advances the practical deployment of AI in extreme environments but also sets a foundation for future work in mobile vision systems, autonomous navigation, and human-robot interaction under uncertainty. His contributions are shaping the next generation of intelligent, life-saving robotic systems.
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Top Papers
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