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A deep learning framework based on improved self‐supervised learning for ground‐penetrating radar tunnel lining inspection

Auteur(s): (School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China)
(School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China)
(School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China)
(School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China)
(China Railway Southwest Research Institute Co. LTD Chengdu China)
(China Railway Southwest Research Institute Co. LTD Chengdu China)
(Remote Sensing Laboratory Bauman Moscow State Technical University Moscow Russia)
(School of Geosciences University of Aberdeen Aberdeen UK)
(Norwegian Geotechnical Institute Oslo Norway)
(Department of Geoscience and Engineering Delft University of Technology Delft The Netherlands)
Médium: article de revue
Langue(s): anglais
Publié dans: Computer-Aided Civil and Infrastructure Engineering, , n. 6, v. 39
DOI: 10.1111/mice.13042
Structurae ne peut pas vous offrir cette publication en texte intégral pour l'instant. Le texte intégral est accessible chez l'éditeur. DOI: 10.1111/mice.13042.
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  • Reference-ID
    10725624
  • Publié(e) le:
    30.05.2023
  • Modifié(e) le:
    15.03.2024
 
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