Papers
1
Total Citations
9
H-Index
1
About
Yu-Shu Yeh is a researcher specializing in autonomous mobile robotics, computer vision, and real-time perception systems. Their most notable contribution is the development of a real-time pedestrian legs detection and tracking system, designed to enhance the safety and navigation capabilities of autonomous mobile robots. By focusing on the lower part of the human body, Yeh’s work addresses a critical challenge in dynamic environments where full-body detection may be obstructed or unreliable. In their highly cited 2017 paper, they rigorously evaluated two classifiers—multilayer perceptron (MLP) and support vector machines (SVM)—to determine the most effective approach for robust, real-time performance. This research has garnered significant attention, accumulating 9 citations and serving as a foundational reference for subsequent studies in human-robot interaction and autonomous navigation. Yeh’s work exemplifies a practical, engineering-driven approach to integrating machine learning with robotic perception, making strides toward safer and more responsive autonomous systems. Their contributions continue to influence the development of intelligent robots capable of operating seamlessly alongside humans in shared spaces.
Research Focus
Key Achievements
Top Papers
- 1