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    Crack Identification and Severity Analysis via Computer Vision: Comparative Study of RGB and Grayscale Imagery

    Source: Journal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 003::page 04026004-1
    Author:
    Fan, Ching-Lung
    DOI: 10.1061/JCEMD4.COENG-16994
    Publisher: American Society of Civil Engineers
    Abstract: AbstractDeep learning–based computer vision technology has become an effective tool for crack detection and segmentation, and it has considerable potential for application in infrastructure maintenance. Crack detection and segmentation are the two core ...Practical ApplicationsIdentifying and measuring cracks in concrete structures is essential for ensuring their safety and longevity. This study presents a practical approach to detecting and analyzing concrete cracks using computer vision technology. By ...
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      Crack Identification and Severity Analysis via Computer Vision: Comparative Study of RGB and Grayscale Imagery

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311097
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    contributor authorFan, Ching-Lung
    date accessioned2026-08-20T10:40:09Z
    date available2026-08-20T10:40:09Z
    date copyright2026/01/06
    date issued2026
    identifier otherJCEMD4.COENG-16994.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311097
    description abstractAbstractDeep learning–based computer vision technology has become an effective tool for crack detection and segmentation, and it has considerable potential for application in infrastructure maintenance. Crack detection and segmentation are the two core ...Practical ApplicationsIdentifying and measuring cracks in concrete structures is essential for ensuring their safety and longevity. This study presents a practical approach to detecting and analyzing concrete cracks using computer vision technology. By ...
    publisherAmerican Society of Civil Engineers
    titleCrack Identification and Severity Analysis via Computer Vision: Comparative Study of RGB and Grayscale Imagery
    typeJournal Article
    journal volume152
    journal issue3
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/JCEMD4.COENG-16994
    journal fristpage04026004-1
    journal lastpage04026004-17
    page17
    treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 003
    contenttypeFulltext
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