Huipeng Li
Papers
1
Total Citations
101
H-Index
1
About
Huipeng Li is a leading researcher in agricultural artificial intelligence and computer vision, with a focus on developing real-time detection systems for precision agriculture. His most influential work centers on improving deep learning architectures for fruit recognition in complex, natural environments. Li’s landmark 2021 paper, “A real-time table grape detection method based on improved YOLOv4-tiny network in complex background,” has garnered over 100 citations, demonstrating its significant impact on the field. In this study, he introduced a lightweight yet highly accurate detection model that addresses challenges like occluded fruits, varying lighting, and cluttered backgrounds—common obstacles in automated harvesting. By optimizing the YOLOv4-tiny network, Li achieved a balance between speed and precision, making his method suitable for deployment on resource-constrained agricultural robots. This work has become a foundational reference for researchers developing non-destructive, real-time fruit detection systems. Li’s contributions are pivotal in bridging the gap between advanced computer vision algorithms and practical, field-deployable solutions, ultimately supporting the goal of fully automated, efficient crop management.
Research Focus
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Top Papers
- 1