Yanyu Chen
Papers
2
Total Citations
31
H-Index
2
About
Yanyu Chen is a researcher focused on agricultural robotics and computer vision, with a particular emphasis on automating strawberry harvesting in complex greenhouse environments. Her work addresses critical challenges in precision agriculture, including fruit ripeness classification and occlusion-robust detection for robotic picking. Chen’s most-cited paper, “Strawberry ripeness classification method in facility environment based on red color ratio of fruit rind” (2023, 29 citations), introduces a simple yet effective color-based approach for determining harvest readiness, providing a practical solution for real-time sorting in controlled environments. Her more recent study, “A lightweight keypoint detection model-based method for strawberry recognition and picking point localization in multi-occlusion scenes” (2025, 2 citations), tackles the pervasive issue of fruit occlusion on elevated growing systems—a major bottleneck for robotic harvesting. By developing a computationally efficient model suitable for embedded devices, Chen enables accurate fruit detection and picking-point localization even when strawberries are partially hidden by leaves or other fruits. This work directly supports the deployment of lightweight, cost-effective picking robots in commercial settings. Chen’s contributions bridge the gap between computer vision theory and agricultural application, offering scalable solutions that improve harvest efficiency and reduce labor dependency.
Research Focus
Key Achievements
Top Papers
- 1
- 2