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Automated Crack Detection via Semantic Segmentation Approaches Using Advanced U-Net Architecture
2022
Intelligent Automation and Soft Computing
Cracks affect the robustness and adaptability of various infrastructures, including buildings, bridge piers, pavement, and pipelines. Therefore, the robustness and the reliability of automated crack detection are essential. In this study, we conducted image segmentation using various crack datasets by applying the advanced architecture of U-Net. First, we collected and integrated crack datasets from prior studies, including the cracks in buildings and pavements. For effective localization and
doi:10.32604/iasc.2022.024405
fatcat:qiyszir4tjan3cmmblelrntjdq