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Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network

Author(s): (School of Civil Engineering and Hunan Provincial Key Laboratory for Disaster Prevention and Mitigation of Rail Transit Engineering Structure Central South University Changsha P. R. China)
(School of Civil Engineering and Hunan Provincial Key Laboratory for Disaster Prevention and Mitigation of Rail Transit Engineering Structure Central South University Changsha P. R. China)
(School of Civil Engineering and Hunan Provincial Key Laboratory for Disaster Prevention and Mitigation of Rail Transit Engineering Structure Central South University Changsha P. R. China)
Medium: journal article
Language(s): English
Published in: Computer-Aided Civil and Infrastructure Engineering, , n. 17, v. 38
Page(s): 2491-2510
DOI: 10.1111/mice.13003
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: 10.1111/mice.13003.
  • About this
    data sheet
  • Reference-ID
    10725620
  • Published on:
    30/05/2023
  • Last updated on:
    14/01/2024
 
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