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Waveform‐based fracture identification of steel beam ends using convolutional neural networks

Author(s): ORCID (Technology Service Department AI Team, Photoruction Co., Ltd Tokyo Japan)
(Department of Civil and Environmental Engineering Saitama University Saitama Japan)
(Division of Architecture and Civil Engineering Ashikaga University Tochigi Japan)
ORCID (Civil Engineering Department International Division, Hazama Ando Corporation Minato Japan)
Medium: journal article
Language(s): English
Published in: Structural Control and Health Monitoring, , n. 9, v. 28
DOI: 10.1002/stc.2777
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1002/stc.2777.
  • About this
    data sheet
  • Reference-ID
    10612477
  • Published on:
    09/07/2021
  • Last updated on:
    26/08/2021
 
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