Rencai Yue
Papers
2
Total Citations
71
H-Index
2
About
Rencai Yue is a leading researcher in precision agriculture and intelligent field robotics, with a focus on computer vision and deep learning for crop management. His work centers on developing lightweight, high-efficiency algorithms for real-time agricultural applications, particularly in seedling detection and navigation. In his highly cited 2024 paper, "Seedling-YOLO," Yue introduced a novel target detection algorithm based on YOLOv7-Tiny, achieving rapid and accurate identification of broccoli seedling transplanting quality—a critical step for robotic field management. This work addresses persistent challenges of false and missed detections in planting quality assessment, garnering 40 citations. Complementing this, his "SN-CNN" paper (31 citations) presents a lightweight convolutional neural network for extracting crop row centerlines in ridge-planted vegetables, enabling precise autonomous navigation during seedling stage field management. Yue's contributions are notable for their practical impact on agricultural automation, offering scalable solutions that balance accuracy with computational efficiency. His research directly supports the advancement of smart farming technologies, making him a key figure in the intersection of deep learning and precision agriculture.
Research Focus
Key Achievements
Top Papers
- 1
- 2