Wenting Qiao
Papers
1
Total Citations
41
H-Index
1
About
Wenting Qiao is a researcher at the intersection of structural engineering and computer vision, whose work focuses on automating infrastructure health monitoring. Her most cited study, "Automatic bridge crack identification from concrete surface using ResNeXt with postprocessing" (2020, 41 citations), tackles the critical challenge of detecting surface cracks—key indicators of structural durability and service performance—in bridge concrete. By applying the deep learning architecture ResNeXt alongside innovative postprocessing techniques, Qiao demonstrates how real-world images can replace inefficient artificial visual inspection, offering a faster, more reliable method for assessing structural integrity. This contribution is particularly impactful for aging infrastructure, where timely crack detection can prevent costly failures. Her research bridges the gap between advanced machine learning and practical civil engineering, providing a scalable solution for automated damage assessment. With growing interest in smart infrastructure, Qiao’s work is poised to influence both academic research and field applications, making her a notable voice in the push toward data-driven structural health monitoring.
Research Focus
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Top Papers
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