Zhenyu Xing
Papers
3
Total Citations
51
H-Index
3
About
Zhenyu Xing is a leading researcher in agricultural robotics, with a specialized focus on the development of intelligent harvesting systems for safflower. His work centers on computer vision, deep learning, and precision localization algorithms to overcome the unique challenges of robotic picking in complex natural environments. Xing’s major contributions include pioneering lightweight yet highly accurate detection models, such as the SDC-DeepLabv3+ and an improved Faster R-CNN with split attention, which enable robots to distinguish safflower filaments from similar-looking organs under varying illumination, occlusion, and weather conditions. He also advanced filament-necking localization by integrating an improved particle swarm optimization with a rotated rectangle algorithm, significantly boosting picking accuracy. Each of his three most-cited papers has garnered 17 citations, reflecting the immediate relevance and impact of his work on the field. Xing’s innovations directly address critical bottlenecks in agricultural automation, offering scalable solutions for high-precision harvesting that could transform safflower cultivation and reduce labor dependency.
Research Focus
Key Achievements
Top Papers
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