Papers
2
Total Citations
21
H-Index
2
About
Yuanyin Luo is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent harvesting systems for specialty crops. His most significant contributions center on the development of deep learning-based detection algorithms for *Camellia oleifera*—a valuable oilseed tree cultivated in complex, unstructured natural environments. Luo’s landmark 2023 paper, “A Trunk Detection Method for Camellia oleifera Fruit Harvesting Robot Based on Improved YOLOv7,” has garnered 19 citations for pioneering a robust, real-time trunk recognition framework that enables harvesting robots to accurately locate vibration or picking points, overcoming the limitations of traditional visual methods that fail in dense foliage and variable lighting. He further refined this approach in 2024, advancing the model’s precision for sustainable agricultural automation. With a cumulative impact demonstrated by these highly cited works, Luo’s research directly addresses critical bottlenecks in robotic fruit harvesting—namely, reliable target detection in natural settings. His work not only enhances the efficiency of *Camellia oleifera* harvesting but also provides a scalable blueprint for applying improved YOLO architectures to other agricultural detection tasks, positioning him as a key innovator at the intersection of AI and precision agriculture.
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