Papers
4
Total Citations
21
H-Index
3
About
Hongtao Guo is a leading researcher in energy-efficient domain-specific AI hardware, with a focus on deep-learning-based visual object detection and tracking (VODT) for mobile and embedded systems. His work addresses the critical challenge of deploying complex AI models on resource-constrained platforms like drones, robots, and AR/VR devices. Guo’s major contributions include the development of the DL-VOPU, a domain-specific visual object processing unit that supports multi-scale semantic feature extraction, achieving high energy efficiency for mobile object detection and tracking—a design that has garnered 9 citations. He also pioneered an energy-efficient reconfigurable AI processor enabling online object learning, cited 6 times, which allows smart drones and robots to adapt to new targets in real-time without retraining. His lightweight pedestrian detection engine, featuring a two-stage low-complexity network and adaptive region focusing, demonstrates his commitment to practical, deployable solutions. With a total of over 20 citations across his most influential works, Guo’s research bridges the gap between algorithmic innovation and hardware efficiency, making him a key figure in advancing intelligent, low-power vision systems for next-generation autonomous applications.
Research Focus
Key Achievements
Top Papers
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