Yankun Peng
Papers
7
Total Citations
131
H-Index
4
About
Dr. Yankun Peng is a leading researcher in agricultural robotics and intelligent weed management, with a primary focus on deep learning and computer vision for precision agriculture. His most impactful work centers on developing optimized YOLO-based convolutional neural networks for real-time identification and localization of weeds and vegetables, particularly in lettuce fields. His landmark 2022 paper on SE-YOLOv5x, which integrates transfer learning and visual attention mechanisms, has garnered 54 citations and addresses the critical challenge of resource competition between crops and weeds. Dr. Peng’s contributions extend to intelligent intra-row weed control, where his lightweight YOLO models enable real-time weed severity classification, and to robotic systems for automatic detection and classification of apple internal quality. His recent work advances variable-rate spraying technologies and fluorescence imaging for crop signaling, demonstrating a trajectory toward fully autonomous, sensor-driven weeding robots. With over 130 total citations and a growing portfolio of high-impact publications, Dr. Peng is shaping the future of smart farming by making weed management more efficient, reducing herbicide reliance, and improving crop yield and quality through cutting-edge artificial intelligence.
Research Focus
Key Achievements
Top Papers
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