Ying‐Bin Liu

Guilin University of Aerospace Technology, Guilin University of Technology

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About

Ying-Bin Liu’s research lies at the intersection of intelligent medical devices and deep learning, with a primary focus on automated acupoint localization for acupuncture robots. His work addresses a critical gap in traditional Chinese medicine technology: the lack of mature, automated methods for identifying acupuncture points on the human body. Liu’s major contributions include developing a back acupoint location method that leverages prior anatomical knowledge and deep learning (9 citations), and a facial acupoint approach using an enhanced Faster PFLD network (5 citations). These innovations enable medical robots to combine acupoint precision with treatment efficacy, advancing auxiliary disease prevention and therapy. Beyond medical applications, Liu has also contributed to industrial vision with GSC-YOLO, a lightweight network for detecting cup and piston heads (3 citations), demonstrating versatility in object detection. His work is notable for bridging traditional medical practices with modern AI, offering practical solutions for robotic-assisted healthcare. With a growing citation impact, Liu’s research is paving the way for smarter, more reliable medical devices that integrate ancient wisdom with cutting-edge technology.