Papers
15
Total Citations
463
H-Index
9
About
Xiaoqiang Du is a leading researcher at the intersection of agricultural robotics, computer vision, and precision farming technologies. His work focuses on developing intelligent detection and automation systems to address critical challenges in modern crop production, with particular emphasis on fruit detection, robotic harvesting, and field navigation. Du's most impactful contributions center on advancing YOLO-based deep learning architectures for agricultural applications. His DSW-YOLO framework for strawberry detection under varying occlusion conditions has garnered 107 citations, while his STRAW-YOLO and YOLOv10/v9-pose models demonstrate his sustained innovation in real-time fruit and stalk pose estimation. His widely cited review of core agricultural robot technologies (92 citations) serves as an essential reference for researchers entering the field. Beyond fruit detection, Du has made significant strides in 3D pose estimation for tomato picking robots, paddy field row detection, fruitlet counting in complex orchard environments, and even early-stage mechanization work including a specialized twining robot for hops production. His research spans nearly a decade of continuous contribution, accumulating over 400 citations across his top works. For students and researchers in agricultural automation, Du's portfolio represents a comprehensive roadmap for deploying AI-driven robotics in real-world farming contexts.
Research Focus
Key Achievements
Top Papers
- 1
- 2A review of core agricultural robot technologies for crop productions92 citations · 2023
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- 6STRAW-YOLO: A detection method for strawberry fruits targets and key points38 citations · 2025
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- 10A Twining Robot for High-Trellis String Tying in Hops Production6 citations · 2012