Papers
12
Total Citations
1,047
H-Index
9
About
Yuzhen Lu is a leading agricultural engineering researcher whose work sits at the intersection of computer vision, robotics, and precision agriculture. Specializing in intelligent systems for crop production, Lu has made transformative contributions to automated weed detection, robotic harvesting, and the broader application of artificial intelligence in farming. Her 2020 survey on public datasets for computer vision in precision agriculture (364 citations) has become an essential reference for researchers entering the field, cataloguing the technological landscape from planting through harvesting. Lu's pioneering benchmark datasets and YOLO-based object detection frameworks — including YOLOWeeds and DeepCottonWeeds — have substantially advanced multi-class weed identification in cotton systems, collectively earning hundreds of citations and providing the research community with critical tools for sustainable, herbicide-reducing weed management. Her work extends beyond software, encompassing the design and field evaluation of robotic cotton harvesting systems, from end-effector engineering to full prototype integration and real-world testing. Additionally, her comprehensive review of mechanical apple harvest technology (137 citations) demonstrates the breadth of her expertise across multiple crops. Through high-impact publications and practical innovations, Lu is shaping the future of autonomous, efficient, and environmentally conscious agriculture.
Research Focus
Key Achievements
Top Papers
- 1A survey of public datasets for computer vision tasks in precision agriculture364 citations · 2020
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- 4Technology progress in mechanical harvest of fresh market apples137 citations · 2020
- 5Opportunities for Robotic Systems and Automation in Cotton Production37 citations · 2021
- 6An end-effector for robotic cotton harvesting32 citations · 2022
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