Yousheng Su
Papers
2
Total Citations
50
H-Index
2
About
Yousheng Su is a leading researcher in smart agriculture and robotic perception, with a core focus on lightweight deep learning models for precision fruit detection and autonomous navigation in complex environments. His most influential work, "GA-YOLO: A Lightweight YOLO Model for Dense and Occluded Grape Target Detection" (2023, 29 citations), addresses a critical bottleneck in agricultural robotics: accurately detecting heavily occluded and clustered fruits in real-world vineyard settings. By optimizing the YOLO architecture for speed and accuracy, Su’s model enables picking robots to overcome missed detections and slow inference, directly advancing the feasibility of automated harvesting. In parallel, his research on path planning—exemplified by "Direction constraints adaptive extended bidirectional A* algorithm based on random two-dimensional map environments" (2023, 21 citations)—introduces adaptive constraints to improve navigation efficiency in unpredictable terrains. Together, these contributions form a dual foundation for intelligent agricultural robots: robust visual perception and efficient motion planning. Su’s work is highly cited for its practical impact, bridging the gap between theoretical computer vision and deployable field robotics, and is essential reading for researchers developing autonomous systems for unstructured agricultural environments.
Research Focus
Key Achievements
Top Papers
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