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    Res-FPN–SqueezeNet Segmentation Architecture for Enhanced Identification of Concrete Cracks within a Deep-Learning Framework

    Source: Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 005::page 04025061-1
    Author:
    Zhang, Chunzheng
    ,
    Mu, Tianwei
    ,
    Ning, Baokuan
    ,
    Wang, Xingkai
    ,
    Ma, Yuan
    DOI: 10.1061/JCCEE5.CPENG-6621
    Publisher: American Society of Civil Engineers
    Abstract: AbstractTo enhance the precision and efficiency of concrete crack detection and segmentation in concrete structures, this paper proposes a novel Res-FPN–SqueezeNet segmentation model improved by the SqueezeNet convolutional neural network based on a deep ...
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      Res-FPN–SqueezeNet Segmentation Architecture for Enhanced Identification of Concrete Cracks within a Deep-Learning Framework

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314405
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    contributor authorZhang, Chunzheng
    contributor authorMu, Tianwei
    contributor authorNing, Baokuan
    contributor authorWang, Xingkai
    contributor authorMa, Yuan
    date accessioned2026-08-20T21:24:31Z
    date available2026-08-20T21:24:31Z
    date copyright2025/06/05
    date issued2025
    identifier otherJCCEE5.CPENG-6621.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314405
    description abstractAbstractTo enhance the precision and efficiency of concrete crack detection and segmentation in concrete structures, this paper proposes a novel Res-FPN–SqueezeNet segmentation model improved by the SqueezeNet convolutional neural network based on a deep ...
    publisherAmerican Society of Civil Engineers
    titleRes-FPN–SqueezeNet Segmentation Architecture for Enhanced Identification of Concrete Cracks within a Deep-Learning Framework
    typeJournal Article
    journal volume39
    journal issue5
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6621
    journal fristpage04025061-1
    journal lastpage04025061-13
    page13
    treeJournal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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