Sheng Wei
Papers
2
Total Citations
57
H-Index
2
About
Sheng Wei is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent fruit detection and automated harvesting systems. His work addresses critical challenges in precision agriculture, particularly the development of robust algorithms for detecting and localizing citrus fruits under complex orchard conditions. Wei's major contributions include pioneering improvements to the You Only Look Once (YOLO) object detection framework—specifically YOLOv5s—to overcome issues like variable illumination and fruit occlusion, achieving high-accuracy detection in real-world environments. His research on binocular vision systems has enabled precise three-dimensional localization of both fruits and picking points, laying the groundwork for fully autonomous harvesting robots. With his most-cited paper accumulating 40 citations and a subsequent 2024 study receiving 17 citations, Wei's work is gaining traction among scholars and engineers developing agricultural automation technologies. His innovative integration of deep learning with stereo vision represents a significant step toward solving one of the most persistent bottlenecks in robotic fruit harvesting, making his research highly relevant for students and researchers interested in smart farming and applied artificial intelligence.
Research Focus
Key Achievements
Top Papers
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- 2