Guanglin Dai
Papers
4
Total Citations
52
H-Index
3
About
Guanglin Dai is a leading researcher in agricultural robotics and precision horticulture, with a primary focus on automating greenhouse operations through computer vision and robotic manipulation. His major contributions center on developing intelligent systems for the selective harvesting and monitoring of high-value crops, particularly cherry tomatoes and other greenhouse fruits. Dai’s pioneering work includes the design and field evaluation of a fully automated selective harvesting robot for cherry tomatoes, which addresses critical labor shortages and rising costs in modern agriculture. He has also advanced fruit maturity detection using deep learning models like YOLOv4 combined with statistical color models, enabling real-time, non-destructive ripeness assessment. His research on robust tomato counting frameworks, leveraging YOLOv8 and inter-frame prediction for greenhouse inspection robots, has set new standards for automated yield estimation and crop monitoring. With his most cited paper garnering 26 citations and a growing portfolio of influential studies, Dai’s work is shaping the future of precision agriculture. His achievements include developing practical, field-tested robotic solutions that bridge the gap between cutting-edge AI and real-world farming challenges, making him a key figure in the transition toward fully automated, data-driven greenhouse management.
Research Focus
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Top Papers
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