Yanqi Bao
Papers
1
Total Citations
100
H-Index
1
About
Yanqi Bao is a leading researcher in robotic visual perception, with a focus on salient object detection (SOD) and multi-modal image processing. Their most cited work, "A Novel Visible-Depth-Thermal Image Dataset of Salient Object Detection for Robotic Visual Perception" (2022), has garnered 100 citations for pioneering a comprehensive dataset that integrates visible, depth, and thermal imagery. This contribution directly addresses a critical gap in robotic grasping applications, enabling faster and more accurate object detection in complex industrial environments. By advancing SOD methods to leverage multi-modal data, Bao's research enhances robotic systems' ability to perceive and interact with their surroundings, particularly in low-visibility or cluttered settings. Their work bridges computer vision and robotics, offering practical solutions for automation and manufacturing. With a citation count reflecting growing influence, Bao continues to drive innovation in visual perception, making their research essential for students and engineers developing next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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