Convolutional neural networks for the detection of damaged fasteners in engineering structures

Gibbons, T.J. orcid.org/0000-0002-5041-7053, Pierce, S., Worden, K. orcid.org/0000-0002-1035-238X et al. (1 more author) (2018) Convolutional neural networks for the detection of damaged fasteners in engineering structures. In: Proceedings of the 9th European workshop on structural health monitoring (EWSHM 2019). 9th European Workshop on Structural Health Monitoring, 10-13 Jul 2018, Manchester, UK. NDT.net .

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2018 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial Licence (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You may not use the material for commercial purposes.
Dates:
  • Published (online): 1 November 2018
  • Published: November 2018
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Sciences Research CouncilEP/N018427/1
Depositing User: Symplectic Sheffield
Date Deposited: 02 Nov 2018 16:14
Last Modified: 02 Nov 2018 16:14
Published Version: https://www.ndt.net/?id=23276
Status: Published
Publisher: NDT.net
Refereed: Yes

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