Yufeng Shu
Papers
2
Total Citations
28
H-Index
2
About
Yufeng Shu is a researcher specializing in machine vision, embedded systems, and agricultural robotics, with a focus on practical applications in industrial inspection and autonomous harvesting. Their most cited work, "Research on detection algorithm of lithium battery surface defects based on embedded machine vision" (2021, 21 citations), addresses a critical manufacturing challenge by replacing manual inspection with an automated, robot-based visual detection system. This innovation significantly reduces human error and workload in high-quality lithium battery production. Shu further extends vision technology to agriculture in "Research on the vision system of lychee picking robot based on stereo vision" (2023, 7 citations), where they develop a stereo vision system for precise fruit identification and picking. This system integrates image acquisition, analysis, and processing, with adaptive correction for varying light conditions. By bridging industrial defect detection and agricultural automation, Shu demonstrates a versatile approach to deploying machine vision in real-world environments. Their work holds promise for enhancing efficiency and accuracy in both manufacturing and food production sectors, making them a notable contributor to applied computer vision research.
Research Focus
Key Achievements
Top Papers
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- 2