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    Multiclass Deep Support Vector Data Description for Structural Health Monitoring

    Source: Journal of Structural Engineering:;2025:;Volume ( 151 ):;issue: 012::page 04025201-1
    Author:
    Lee, Yeong In
    ,
    Lee, Sang Min
    ,
    Kang, Thomas H.-K.
    DOI: 10.1061/JSENDH.STENG-14823
    Publisher: American Society of Civil Engineers
    Abstract: AbstractEnsuring the structural integrity of building is critical for maintaining public safety, necessitating reliable methods for the detection of internal defects. In practice, however, obtaining data from compromised structures poses significant ...
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      Multiclass Deep Support Vector Data Description for Structural Health Monitoring

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4313398
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    • Journal of Structural Engineering

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    contributor authorLee, Yeong In
    contributor authorLee, Sang Min
    contributor authorKang, Thomas H.-K.
    date accessioned2026-08-20T12:21:41Z
    date available2026-08-20T12:21:41Z
    date copyright2025/09/27
    date issued2025
    identifier otherJSENDH.STENG-14823.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313398
    description abstractAbstractEnsuring the structural integrity of building is critical for maintaining public safety, necessitating reliable methods for the detection of internal defects. In practice, however, obtaining data from compromised structures poses significant ...
    publisherAmerican Society of Civil Engineers
    titleMulticlass Deep Support Vector Data Description for Structural Health Monitoring
    typeJournal Article
    journal volume151
    journal issue12
    journal titleJournal of Structural Engineering
    identifier doi10.1061/JSENDH.STENG-14823
    journal fristpage04025201-1
    journal lastpage04025201-14
    page14
    treeJournal of Structural Engineering:;2025:;Volume ( 151 ):;issue: 012
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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