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    CMCAB: An Insertable Block for Concrete Crack Detection Based on Masked Convolution Attention

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    JCCEE5.CPENG-7088.pdf (1.986Mb)
    Date
    2026
    Author
    Ma, Yu
    Cui, Benben
    Jiang, Wen
    Yan, Laibao
    Cui, Xiaotian
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    Abstract
    AbstractCracks are frequent defects that pose significant potential threats to structural safety and property. Due to the inefficiency of traditional crack detection methods, deep learning techniques—particularly convolutional neural networks—have become ...Practical ApplicationsThis study proposes a pluggable crack detection module designed for concrete structures. The module can function as a standalone detection model or be seamlessly integrated into existing detection frameworks. It enhances the ...
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4314481
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