Papers
2
Total Citations
12
H-Index
2
About
Xiaoming Wei is a leading researcher in agricultural robotics and intelligent detection systems, with a focus on automating labor-intensive tasks in modern horticulture. His work addresses critical challenges in vegetable grafting and crop monitoring, combining mechanical design with deep learning to improve efficiency and precision. Wei’s most cited paper, “Design and Experiment of Automatic Clip-Feeding Mechanism for Vegetable-Grafting Robot” (2022, 9 citations), tackles the poor stability and performance of automatic clip-feeding in grafting machines. He developed a novel mechanism with a precise single-clip discharge system, validated through rigorous testing, directly enhancing the reliability of robotic grafting—a key bottleneck in automated seedling production. More recently, his 2025 study, “Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8” (3 citations), advances computer vision for agriculture. By optimizing YOLOv8 for robust detection of tomato flower buds in complex, multi-environmental settings, Wei provides a vital tool for yield prediction and precision management. His work bridges mechanical engineering and AI, offering practical solutions that reduce labor dependency and improve crop quality. With a growing citation record and a focus on real-world deployment, Wei is establishing himself as an innovator at the intersection of robotics and agricultural science.
Research Focus
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Top Papers
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