Shouxiang Jin
Papers
2
Total Citations
53
H-Index
2
About
Shouxiang Jin is a leading researcher in agricultural robotics and precision harvesting, with a primary focus on the mechanized picking of Camellia oleifera fruit. His work addresses critical challenges in robotic vision and manipulation for specialty crops. Jin’s major contributions center on developing intelligent systems for fruit detection, spatial positioning, and posture determination. His 2024 paper on "3D positioning of Camellia oleifera fruit-grabbing points for robotic harvesting" (28 citations) provides a foundational method for accurately locating harvest targets in complex orchard environments. Building on this, his 2025 work "CO-YOLO: A lightweight and efficient model for Camellia oleifera fruit object detection and posture determination" (25 citations) introduces a novel deep-learning architecture that balances detection accuracy with computational efficiency—essential for real-time field deployment. Together, these highly cited studies demonstrate Jin’s impact on advancing automated harvesting technology, reducing labor dependency, and improving fruit quality. His research is pivotal for the agricultural robotics community, offering practical solutions that bridge computer vision and mechanical harvesting.
Research Focus
Key Achievements
Top Papers
- 1
- 2