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Autonomous detection of damage to multiple steel surfaces from 360° panoramas using deep neural networks

Auteur(s): (College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China)
(Department of Design, Manufacturing & Engineering Management University of Strathclyde Glasgow UK)
(School of Mechanical Engineering Xi''an Jiaotong University Shaanxi China)
(College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China)
(College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China)
(School of Computer Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing China)
(Department of Design, Manufacturing & Engineering Management University of Strathclyde Glasgow UK)
(College of Mechanical and Electronic Engineering China University of Petroleum (East China) Qingdao China)
Médium: article de revue
Langue(s): anglais
Publié dans: Computer-Aided Civil and Infrastructure Engineering, , n. 12, v. 36
Page(s): 1585-1599
DOI: 10.1111/mice.12686
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.12686.
  • Informations
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  • Reference-ID
    10601280
  • Publié(e) le:
    17.04.2021
  • Modifié(e) le:
    29.11.2021
 
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