Yinsong Zhang
Papers
1
Total Citations
41
H-Index
1
About
Yinsong Zhang is a leading researcher in agricultural robotics and computer vision, with a primary focus on intelligent tea harvesting systems. His most cited work, "Edge Device Detection of Tea Leaves with One Bud and Two Leaves Based on ShuffleNetv2-YOLOv5-Lite-E" (2023, 41 citations), addresses a critical bottleneck in automated tea picking: the accurate, real-time recognition of premium tea shoots on resource-constrained edge devices. Zhang’s major contribution lies in optimizing deep learning architectures for practical deployment—specifically, replacing standard feature extraction networks with lightweight alternatives to enable high-speed, precise detection directly on picking robots. This innovation bridges the gap between theoretical computer vision and field-ready agricultural automation, significantly improving the efficiency and selectivity of mechanical tea harvesting. By demonstrating that sophisticated object detection can run on low-power hardware without sacrificing accuracy, Zhang has opened new pathways for smart agriculture in remote or resource-limited settings. His work not only advances precision agriculture but also addresses labor shortages in tea-producing regions, making him a pivotal figure in the intersection of AI and sustainable farming.
Research Focus
Key Achievements
Top Papers
- 1