Papers
1
Total Citations
58
H-Index
1
About
Xuebin Qi is a leading researcher at the intersection of computer vision and precision agriculture, with a primary focus on developing lightweight, high-efficiency deep learning algorithms for intelligent crop monitoring and robotic harvesting. His most impactful contribution is the "Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory" (2023), which has garnered 58 citations for its innovative approach to enabling accurate, real-time fruit detection on resource-constrained devices. This work directly addresses the critical need for deploying advanced detection technology in modern plant factories, where robots and mobile terminals must operate with both speed and precision. By optimizing the YOLOv5 architecture for agricultural environments, Qi’s algorithm significantly reduces computational load without sacrificing detection accuracy, making it a foundational tool for the development of intelligent and precision agriculture. His research is pivotal in bridging the gap between state-of-the-art computer vision and practical, on-field agricultural automation, empowering the next generation of smart farming solutions.
Research Focus
Key Achievements
Top Papers
- 1Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory58 citations · 2023