Reconstruction of concrete morphology using deep learning

dc.contributor.author	Šperl, Ondřej
dc.contributor.author	Sýkora, Jan
dc.date.accessioned	2024-12-09T11:02:51Z
dc.date.available	2024-12-09T11:02:51Z
dc.date.issued	2024
dc.identifier.citation	Acta Polytechnica. 2024, vol. 49, no. , p. 85-91.
dc.identifier.issn	1210-2709 (print)
dc.identifier.issn	1805-2363 (online)
dc.identifier.uri	http://hdl.handle.net/10467/119727
dc.description.abstract	In this contribution, the concrete morphology is reconstructed with a simple algorithm selecting a pixel value based on the small set of surrounding pixels. A deep neural network (DNN) is used as a classifier, and the authors focus on studying different DNN architectures. The performance of the proposed algorithm is evaluated on several statistical descriptors and the grain size distribution curve.	en
dc.format.mimetype	application/pdf
dc.language.iso	eng
dc.publisher	České vysoké učení technické v Praze	cs
dc.publisher	Czech Technical University in Prague	en
dc.relation.ispartofseries	Acta Polytechnica
dc.relation.uri	https://ojs.cvut.cz/ojs/index.php/APP/article/view/10214
dc.rights	Creative Commons Attribution 4.0 International License	en
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.title	Reconstruction of concrete morphology using deep learning
dc.type	article	en
dc.date.updated	2024-12-09T11:02:51Z
dc.identifier.doi	10.14311/APP.2024.49.0085
dc.rights.access	openAccess
dc.type.status	Peer-reviewed
dc.type.version	publishedVersion

Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International License