Yucheng Xiu
Papers
1
Total Citations
1
H-Index
1
About
Yucheng Xiu is a rising researcher at the intersection of artificial intelligence, smart agriculture, and supply chain cyber security. His work focuses on developing novel deep learning architectures for agronomic applications, particularly in the domain of visual perception for unmanned agricultural robots. Xiu’s most cited paper, “GDMR-Net: A Novel Graphic Detection Neural Network via Multi-Crossed Attention and Rotation Annotation for Agronomic Applications in Supply Cyber Security” (2023), introduces an innovative neural network that leverages multi-crossed attention mechanisms and rotation-aware annotation to enhance object detection in complex agricultural environments. This contribution directly addresses the critical need for robust, intelligent systems that can secure agricultural supply chains by enabling precise, real-time monitoring through IoT-integrated robotic platforms. While his citation count is currently modest—reflecting the recency of his work—Xiu’s research is positioned at the forefront of a rapidly evolving field, where cyber-physical systems and AI converge to safeguard global food production. His work exemplifies how cutting-edge computer vision techniques can be tailored for domain-specific challenges, offering a blueprint for future research in secure, automated agriculture.
Research Focus
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Top Papers
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