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A new deep learning-based approach for concrete crack identification and damage assessment

Author(s): ORCID (School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin, China)
(School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin, China)
(School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin, China)
(School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin, China)
ORCID (School of Civil Engineering, Tianjin Chengjian University, Tianjin, China)
ORCID (School of Civil and Environmental Engineering, University of Technology Sydney, NSW, Australia)
(School of Control and Mechanical Engineering, Tianjin Chengjian University, Tianjin, China)
Medium: journal article
Language(s): English
Published in: Advances in Structural Engineering, , n. 13, v. 27
Page(s): 2303-2318
DOI: 10.1177/13694332241266535
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: 10.1177/13694332241266535.
  • About this
    data sheet
  • Reference-ID
    10791769
  • Published on:
    01/09/2024
  • Last updated on:
    20/09/2024
 
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