Xiaofan Yang
Papers
1
Total Citations
88
H-Index
1
About
Xiaofan Yang is a leading researcher in agricultural robotics and computer vision, with a focus on automating fruit harvesting in complex outdoor environments. Her most cited work, "A mango picking vision algorithm on instance segmentation and key point detection from RGB images in an open orchard" (2021, 88 citations), introduces a pioneering approach that combines instance segmentation with key point detection to precisely locate and identify mangoes for robotic picking. This contribution addresses a critical challenge in precision agriculture: enabling machines to perceive and interact with unstructured, natural scenes. Yang’s algorithm significantly improves detection accuracy and robustness under varying lighting and occlusion conditions, advancing the feasibility of autonomous harvesting systems. Her research has been widely recognized, with this paper alone accumulating 88 citations, reflecting its impact on both the computer vision and agricultural engineering communities. By bridging deep learning techniques with real-world agricultural needs, Yang is helping to shape the future of sustainable farming and food production.
Research Focus
Key Achievements
Top Papers
- 1