Siamese Convolutional Neural Networks to Quantify Crack Pattern Similarity in Masonry Facades
Auteur(s): |
Árpád Rózsás
(Department of Structural Reliability, TNO Building, Infrastructure, and Maritime, Delft, The Netherlands)
Arthur Slobbe (Department of Structural Reliability, TNO Building, Infrastructure, and Maritime, Delft, The Netherlands) Wyke Huizinga (Department of Intelligent Imaging, TNO Defense, Safety, and Security, The Hague, The Netherlands) Maarten Kruithof (Department of Intelligent Imaging, TNO Defense, Safety, and Security, The Hague, The Netherlands) Krishna Ajithkumar Pillai (Department of Structural Reliability, TNO Building, Infrastructure, and Maritime, Delft, The Netherlands) Kelvin Kleijn (Department of Intelligent Imaging, TNO Defense, Safety, and Security, The Hague, The Netherlands) Giorgia Giardina (Department of Geoscience and Engineering, Delft University of Technology, Delft, The Netherlands) |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | International Journal of Architectural Heritage, novembre 2023, n. 1, v. 17 |
Page(s): | 1-23 |
DOI: | 10.1080/15583058.2022.2134062 |
- Informations
sur cette fiche - Reference-ID
10697022 - Publié(e) le:
12.12.2022 - Modifié(e) le:
20.02.2023