Yangang Yang

Tianjin University of Technology and Education

Papers

Total Citations

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About

Yangang Yang is a researcher at the forefront of intelligent robotics and computer vision, with a focus on industrial automation and environmental sustainability. His work centers on developing advanced object detection and dynamic tracking methods to solve real-world challenges in automated disassembly and waste management. Yang’s major contributions include a novel vehicle door frame positioning method for binocular vision robots, leveraging an improved YOLOv4 network to enable fast and accurate grasping of end-of-life cars—a critical step toward automating the recycling process. This work has garnered 7 citations, highlighting its practical impact. He has also pioneered a dynamic tracking technique for coded targets under complex background noise (4 citations), enhancing robotic precision in cluttered environments. Most recently, Yang introduced YOLO-VG, an efficient real-time recyclable waste detection network (2 citations), furthering the application of AI in sustainable waste sorting. His research not only advances robotic perception but also directly supports circular economy goals, making him a notable figure in applied computer vision and green automation.