Sihan Yang
Papers
1
Total Citations
4
H-Index
1
About
Sihan Yang is a researcher at the forefront of robotic manipulation and computer vision, with a particular focus on advancing prosthetic hand technology. Their key research areas include grasp detection, pose estimation, and the innovative use of hybrid vision systems for real-world object interaction. Yang’s major contribution lies in developing a hybrid frame-event solution that overcomes the limitations of traditional frame-based cameras—such as high spatiotemporal redundancy—enabling more efficient and accurate grasp and pose detection in cluttered, dynamic environments. This work, published in 2020 and garnering 4 citations, addresses a critical challenge in mobile robotics and assistive technology, where low-latency, low-power vision is essential. Yang’s approach integrates event-based sensors with conventional cameras, paving the way for more responsive and adaptable prosthetic hands. By tackling the intersection of vision and manipulation, Yang’s research holds promise for enhancing the autonomy and dexterity of robotic systems in real-world settings, making their work a valuable reference for students and researchers exploring next-generation robotic perception and control.
Research Focus
Key Achievements
Top Papers
- 1