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About

Mingyong Li is an emerging researcher at the intersection of agricultural robotics, computer vision, and intelligent automation, with a focus on transforming modern facility agriculture through cutting-edge technology. His work addresses some of the most pressing challenges in precision agriculture, including the development of autonomous systems capable of performing delicate tasks with high efficiency and minimal crop damage. Li's most recognized contribution is his work on visual perception-enabled agricultural intelligence, particularly his 2024 paper on selective seedling picking and transplanting robots, which has already garnered 12 citations — a strong indicator of its relevance to the field. Building on this foundation, his research into Kinect-based visual processing for obstacle avoidance during transplanting demonstrates a sustained commitment to reducing plant damage rates and improving transplanting quality in greenhouse environments. Beyond transplanting systems, Li has expanded his research into intelligent pollination robotics for facility tomatoes and explored advanced image retrieval techniques through fine-tuned CLIP models, reflecting a broader interest in applying deep learning to real-world agricultural challenges. His interdisciplinary approach — bridging robotics, visual computing, and precision agriculture — positions him as a promising contributor to the future of smart, automated farming systems.