Zhijing Shen
Papers
1
Total Citations
9
H-Index
1
About
Dr. Zhijing Shen is a leading researcher in structural health monitoring and computer vision, with a primary focus on advancing automated inspection techniques for civil infrastructure. Her most impactful work centers on integrating deep learning and binocular vision to enhance the accuracy and practicality of crack detection in concrete bridges. In her highly cited 2023 study, she pioneered a method that combines semantic segmentation with binocular vision, enabling not only precise pixel-level crack identification but also reliable three-dimensional measurement of crack morphology—a critical improvement over prior monocular approaches. This work has garnered 9 citations in just its first year, reflecting its immediate relevance to both academia and industry. Dr. Shen’s contributions address a key gap in infrastructure assessment: moving beyond simple detection to quantitative evaluation of crack characteristics, which are essential for accurate condition ratings. Her research promises to reduce reliance on manual inspections, improve safety, and extend the service life of aging bridge networks.
Research Focus
Key Achievements
Top Papers
- 1