Yunhui Yan
Papers
19
Total Citations
461
H-Index
12
About
Yunhui Yan is a prominent researcher specializing in robotic visual perception, intelligent grasping detection, and industrial automation. His work sits at the intersection of computer vision and robotics, with a particular focus on enabling robots to perceive, understand, and interact with complex real-world environments. Yan's most influential contributions include the development of novel multimodal datasets and detection frameworks for salient object detection, most notably a visible-depth-thermal image dataset that has garnered over 100 citations and become a foundational resource for the robotics vision community. His comprehensive review of data-driven robotic visual grasping detection (59 citations) has served as an important reference for researchers navigating this rapidly evolving field. He has also made significant algorithmic contributions, including lightweight RGB-D fusion networks for generative grasping detection, semantic segmentation-guided grasping for weakly textured objects, and simultaneous instance segmentation and grasp detection in cluttered environments. Beyond grasping, Yan has advanced motion planning through his Informed Anytime Fast Marching Tree algorithm and tackled industrial inspection challenges including steel pipe defect detection and autonomous analog meter reading. With over 370 cumulative citations across his most prominent works, Yunhui Yan has established himself as a versatile and impactful contributor to intelligent robotics and industrial visual perception.
Research Focus
Key Achievements
Top Papers
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