Papers
2
Total Citations
231
H-Index
2
About
Maozhen Li is a leading researcher in agricultural robotics and computer vision, with a primary focus on automating high-value crop harvesting. His work centers on the intersection of deep learning, precision agriculture, and robotic manipulation to solve complex, real-world agricultural challenges. Li’s major contributions lie in developing end-to-end systems for the automatic plucking of tender tea shoots, a task requiring exceptional visual precision and delicate handling. His most cited work, "Tender Tea Shoots Recognition and Positioning for Picking Robot Using Improved YOLO-V3 Model" (2019, 125 citations), pioneered the use of an enhanced deep convolutional neural network to accurately identify and locate optimal picking points on tea plants. He further advanced this field with "Computer vision-based high-quality tea automatic plucking robot using Delta parallel manipulator" (2021, 106 citations), which integrated his vision system with a high-speed Delta robot for complete, non-destructive harvesting. These works have established a new benchmark for intelligent tea plucking, demonstrating how AI-driven robotics can improve both the quality and efficiency of premium tea production, with significant implications for the future of automated agriculture.
Research Focus
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Top Papers
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