Papers
2
Total Citations
325
H-Index
2
About
Yunqi Zhang is a leading researcher in agricultural robotics and intelligent vision systems, with a primary focus on automated fruit detection and harvesting for specialty crops. His work addresses the critical challenge of developing robust perception algorithms for complex orchard environments, particularly for *Camellia oleifera*—a high-value oilseed crop where fruits, leaves, and flowers share similar colors and often appear simultaneously. Zhang’s major contributions include pioneering the integration of lightweight deep learning models with classical image processing techniques for real-time fruit positioning. His most cited paper, "Fruit detection and positioning technology for a *Camellia oleifera* C. Abel orchard based on improved YOLOv4-tiny model and binocular stereo vision" (2022, 248 citations), demonstrates a highly efficient detection system that balances accuracy and computational speed. Building on this, his "Adaptive Active Positioning of *Camellia oleifera* Fruit Picking Points: Classical Image Processing and YOLOv7 Fusion Algorithm" (2022, 77 citations) introduces an innovative fusion approach to resolve ambiguities caused by occlusion and simultaneous flowering. This work is critical for minimizing flower damage during mechanical harvesting—a key economic concern. With over 325 combined citations, Zhang’s research is shaping the next generation of precision agriculture, enabling robots to operate reliably in visually challenging, unstructured orchard environments.
Research Focus
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