Chuan Yue
Papers
1
Total Citations
13
H-Index
1
About
Chuan Yue is a researcher at the forefront of intelligent structural health monitoring, specializing in computer vision, deep learning, and automated defect inspection. His work addresses the critical challenge of detecting and quantifying slender cracks in high-resolution images—a task that has long stymied conventional methods due to complex boundaries and prohibitive computational costs. In his landmark 2025 paper, Yue introduced a novel crack detection and quantification framework that leverages the Mamba architecture and unmanned devices, achieving superior segmentation accuracy while dramatically reducing computational overhead. This work, already garnering 13 citations shortly after publication, demonstrates his ability to bridge the gap between cutting-edge AI and practical engineering needs. By enabling real-time, high-precision inspection of infrastructure, Yue’s contributions hold significant promise for enhancing safety and reducing maintenance costs in civil engineering. His research stands out for its technical rigor and direct applicability, marking him as an emerging leader in the field of vision-based structural defect analysis.
Research Focus
Key Achievements
Top Papers
- 1