Xiangrong Li
Papers
1
Total Citations
125
H-Index
1
About
Xiangrong Li is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent harvesting systems. His most impactful work centers on the development of deep learning models for precise crop recognition and positioning, particularly in specialty crops. His landmark 2019 paper, "Tender Tea Shoots Recognition and Positioning for Picking Robot Using Improved YOLO-V3 Model," has garnered 125 citations, establishing a foundational method for automated tea harvesting. In this work, Li pioneered an end-to-end approach using an enhanced YOLO-v3 deep convolutional neural network to accurately identify tender tea shoots and determine optimal picking points in real time. This contribution directly addresses the critical challenge of selective harvesting for high-quality tea, enabling robots to distinguish between leaves of varying maturity. By bridging advanced object detection algorithms with practical agricultural needs, Li's research has significantly advanced the field of precision agriculture, offering scalable solutions for labor-intensive picking tasks and setting a benchmark for future work in robotic crop harvesting.
Research Focus
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Top Papers
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