Papers
8
Total Citations
169
H-Index
6
About
Dr. Yinfa Yan is a leading researcher at the intersection of agricultural engineering and artificial intelligence, with a primary focus on smart agriculture, computer vision, and robotic harvesting systems. His most significant contributions lie in developing deep learning-based methods for fruit maturity classification and recognition in complex natural environments. Dr. Yan’s work on tomato maturity classification using the SE-YOLOv3-MobileNetV1 network (62 citations) and improved apple fruit target recognition based on YOLOv7 (55 citations) has set new benchmarks for accuracy in automated agricultural inspection. He has also pioneered the application of triboelectric nanogenerators for self-powered, flexible force-sensing sensors, enabling non-destructive harvesting of fresh produce—a notable innovation that bridges materials science and agricultural robotics. Beyond fruit handling, Dr. Yan has advanced dairy farm automation through research on navigation path extraction and obstacle avoidance for pusher robots using binocular vision and multi-task convolutional neural networks. His work on apple harvesting robots integrates fruit recognition, task planning, and control, showcasing a holistic approach to agricultural robotics. With over 170 total citations and a growing portfolio of high-impact publications, Dr. Yan is establishing himself as a key innovator in precision agriculture and intelligent harvesting systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Improved Apple Fruit Target Recognition Method Based on YOLOv7 Model55 citations · 2023
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- 7Fruit recognition, task plan, and control for apple harvesting robots3 citations · 2024
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