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    A Three-Stage Intelligent Crack Detection Method for Concrete Bridges Based on Deep Neural Networks

    Source: Journal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 006::page 04026067-1
    Author:
    Zhao, Wenzhuo
    ,
    Li, Ke
    ,
    Liu, Gang
    ,
    Chen, Bin
    ,
    Fan, Mingyu
    ,
    Yin, Shuohui
    DOI: 10.1061/JCEMD4.COENG-17156
    Publisher: American Society of Civil Engineers
    Abstract: AbstractCrack detection is a critical task in the diagnosis and assessment of bridge health. Currently, most crack detection methods concentrate solely on a single aspect (segmentation, object detection, or classification) and are incapable of fulfilling ...
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      A Three-Stage Intelligent Crack Detection Method for Concrete Bridges Based on Deep Neural Networks

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311120
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    • Journal of Construction Engineering and Management

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    contributor authorZhao, Wenzhuo
    contributor authorLi, Ke
    contributor authorLiu, Gang
    contributor authorChen, Bin
    contributor authorFan, Mingyu
    contributor authorYin, Shuohui
    date accessioned2026-08-20T10:41:10Z
    date available2026-08-20T10:41:10Z
    date copyright2026/04/07
    date issued2026
    identifier otherJCEMD4.COENG-17156.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311120
    description abstractAbstractCrack detection is a critical task in the diagnosis and assessment of bridge health. Currently, most crack detection methods concentrate solely on a single aspect (segmentation, object detection, or classification) and are incapable of fulfilling ...
    publisherAmerican Society of Civil Engineers
    titleA Three-Stage Intelligent Crack Detection Method for Concrete Bridges Based on Deep Neural Networks
    typeJournal Article
    journal volume152
    journal issue6
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/JCEMD4.COENG-17156
    journal fristpage04026067-1
    journal lastpage04026067-14
    page14
    treeJournal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 006
    contenttypeFulltext
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