Yuan Liang Huang
Papers
2
Total Citations
37
H-Index
2
About
Yuan Liang Huang is a robotics and computer vision researcher whose work focuses on intelligent agricultural automation and service robotics. His primary research areas include deep learning-based object detection, robotic vision systems, and autonomous navigation for specialized robots. Huang’s most impactful contribution is a real-time Zanthoxylum (prickly ash) target detection method for intelligent picking robots, published in 2022. This work, which has garnered 34 citations, addresses the critical challenge of detecting fruit obscured by branches and leaves in complex natural environments by improving the YOLOv5s architecture. The algorithm significantly enhances the adaptability and efficiency of pepper-picking robots, directly supporting precision agriculture. Earlier, Huang developed a vision orientation system for glass curtain wall cleaning robots using OpenCV, applying edge detection and Hough transforms to guide autonomous navigation. Though less cited, this work demonstrates his versatility in applying computer vision to practical robotic challenges. Huang’s research bridges the gap between advanced deep learning techniques and real-world robotic applications, making him a notable contributor to agricultural robotics and automated inspection systems.
Research Focus
Key Achievements
Top Papers
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- 2