Yiyan Fan
Papers
1
Total Citations
6
H-Index
1
About
Yiyan Fan is a researcher at the forefront of precision agriculture and deep learning, with a focused expertise in automated viticulture. Her most cited work, "Detection and location of wine grape (Cabernet Sauvignon) picking points by using a dual-stage deep learning method" (2025, 6 citations), introduces a pioneering approach to robotic harvesting. By developing a two-stage neural network that first identifies grape clusters and then precisely localizes optimal picking points, Fan addresses a critical bottleneck in agricultural automation—the need for accurate, non-destructive fruit detection in complex vineyard environments. This contribution is particularly significant for high-value crops like Cabernet Sauvignon, where manual picking is labor-intensive and costly. Though early in her career, her work has already garnered attention for its practical implications in reducing harvest waste and improving efficiency. Fan’s research bridges computer vision and agricultural engineering, offering a scalable solution for smart farming. Her methodology, combining object detection with fine-grained point localization, sets a benchmark for future studies in robotic fruit picking and positions her as an emerging leader in the intersection of AI and sustainable agriculture.
Research Focus
Key Achievements
Top Papers
- 1