Probabilistic cracking prediction via deep learned electrical tomography

Chen, L., Gallet, A., Huang, S.-S. et al. (2 more authors) (2022) Probabilistic cracking prediction via deep learned electrical tomography. Structural Health Monitoring, 21 (4). pp. 1574-1589. ISSN 1475-9217

Abstract

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Item Type: Article
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© 2021 The Authors. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Keywords: Artificial Intelligence; Deep learning; Electrical Resistance Tomography; Inverse Problems; Neural Networks; Structural Health Monitoring
Dates:
  • Published: 1 July 2022
  • Published (online): 10 August 2021
  • Accepted: 7 July 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 21 Jul 2021 09:55
Last Modified: 23 Jun 2022 09:00
Status: Published
Publisher: SAGE Publications
Refereed: Yes
Identification Number: 10.1177/14759217211037236
Open Archives Initiative ID (OAI ID):

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