Concrete Structure

Research on concrete structures is increasingly focused on developing automated inspection and damage assessment methods using computer vision and robotics. Current efforts leverage deep learning models, such as U-Net, YOLO, and DeepLab, along with novel approaches like the Segment Anything Model (SAM), to analyze images and videos for crack detection and displacement measurement, improving the accuracy and efficiency of damage identification. This work is driven by the need for faster, more reliable structural assessments, particularly in post-disaster scenarios and for improving the efficiency of construction and maintenance processes. The ultimate goal is to enhance safety, reduce costs, and improve the longevity of concrete infrastructure.