Yingmiao Su
Papers
1
Total Citations
2
H-Index
1
About
Yingmiao Su is a researcher specializing in agricultural computer vision and deep learning, with a particular focus on nighttime fruit detection and segmentation. Their most notable contribution is the development of AP-UNet, a novel deep learning architecture designed to identify guava and its fruit stems in low-light environments. This work, published in 2025 and already garnering 2 citations, addresses a critical challenge in precision agriculture: enabling automated harvesting systems to operate effectively after dark. By adapting the UNet framework with attention mechanisms, Su’s model achieves robust segmentation of both fruit and stem, which is essential for robotic picking without damaging crops. The research has immediate practical implications for improving harvest efficiency and reducing labor costs in tropical fruit farming. Su’s work stands out for its targeted application to a real-world agricultural problem, demonstrating how computer vision can be tailored to specific environmental constraints. As nighttime farming operations become more prevalent, Su’s contributions are poised to influence the design of future autonomous agricultural systems.
Research Focus
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Top Papers
- 1