Yuanxue Xin
Papers
1
Total Citations
10
H-Index
1
About
Dr. Yuanxue Xin is a leading researcher in computer vision and structural health monitoring, with a primary focus on intelligent infrastructure inspection. Her work centers on developing advanced deep learning methods for automated defect detection in challenging environments, particularly underwater. Dr. Xin’s most notable contribution is the development of **CrackInst**, a real-time instance segmentation method specifically designed for identifying cracks in underwater dam surfaces. This work, published in 2024 and already garnering 10 citations, addresses a critical safety need by enabling underwater robots to autonomously detect structural flaws, moving beyond traditional semantic segmentation approaches that lack the precision required for individual crack analysis. Her research bridges the gap between state-of-the-art computer vision and practical civil engineering challenges, offering robust solutions for quality assurance in hydraulic infrastructure. By tackling the unique difficulties of underwater imaging—such as poor visibility and variable lighting—Dr. Xin’s methods enhance the reliability and efficiency of automated inspections. Her work is highly relevant for researchers and engineers in structural health monitoring, robotics, and applied AI, promising safer and more cost-effective maintenance of critical water infrastructure worldwide.
Research Focus
Key Achievements
Top Papers
- 1