Yuhui Yuan
Papers
2
Total Citations
10
H-Index
2
About
Dr. Yuhui Yuan is a researcher whose work lies at the intersection of computer vision and precision agriculture, with a specific focus on intelligent fruit detection. Her primary research areas include deep learning-based object detection, lightweight neural network architectures, and the challenging problem of occluded and overlapping target recognition in agricultural settings. Dr. Yuan's most significant contributions involve advancing the accuracy and efficiency of apple detection systems. Her highly cited 2024 paper, "A lightweight method for apple-on-tree detection based on improved YOLOv5," which has garnered 7 citations, presents a novel approach that balances real-time performance with detection precision, making it suitable for deployment on resource-constrained devices. In a complementary study, "A detection method for occluded and overlapped apples under close-range targets" (3 citations), she tackles a critical bottleneck in automated harvesting: accurately identifying fruit that is partially hidden or clustered. This work demonstrates her ability to address real-world complexities in orchard environments. Dr. Yuan's research is paving the way for more robust and practical robotic harvesting systems, directly impacting the efficiency of modern agriculture.
Research Focus
Key Achievements
Top Papers
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- 2