Hsuan Lee
Papers
1
Total Citations
7
H-Index
1
About
Hsuan Lee is a robotics researcher whose work focuses on real-time object recognition and perception systems for autonomous service robots. In his most-cited paper, “Implementation of real-time object recognition system for home-service robot by integrating SURF and BRISK” (2014, 7 citations), Lee proposed a novel hybrid approach that combines the strengths of SURF and BRISK feature descriptors to enable robots to both recognize known objects and search for unknown ones in dynamic home environments. A key contribution was his integration of Compute Unified Device Architecture (CUDA) for GPU acceleration, achieving real-time performance critical for practical deployment. This work addresses a fundamental challenge in assistive robotics: balancing computational efficiency with recognition accuracy. While his citation count is modest, Lee’s research represents an important step toward making home-service robots more autonomous and responsive to unstructured environments. His approach to fusing multiple feature extraction methods and leveraging parallel computing continues to inform subsequent work in embedded vision systems for robotics.
Research Focus
Key Achievements
Top Papers
- 1