Automated detection of subsurface defects using active thermography and deep learning object detectors

dc.contributor.author	González Lema, Darío
dc.contributor.author	Díaz Pedrayes, Óscar
dc.contributor.author	Usamentiaga Fernández, Rubén
dc.contributor.author	Venegas, P.
dc.contributor.author	García Martínez, Daniel Fernando
dc.date.accessioned	2022-11-08T12:42:34Z
dc.date.available	2022-11-08T12:42:34Z
dc.date.issued	2022
dc.identifier.citation	IEEE Transactions on Instrumentation and Measurement, 71 (2022); doi:10.1109/TIM.2022.3169484
dc.identifier.issn	0018-9456
dc.identifier.uri	http://hdl.handle.net/10651/65333
dc.description.sponsorship	Spanish National Plan for Research, Development and Innovation [RTI2018-094849-B-I00]
dc.language.iso	eng
dc.relation.ispartof	IEEE Transactions on Instrumentation and Measurement
dc.rights	© 2022 IEEE
dc.rights	CC Reconocimiento – No Comercial – Sin Obra Derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128667970&doi=10.1109%2fTIM.2022.3169484&partnerID=40&md5=45889bccaed2f6a2acd38645f8d5200a
dc.title	Automated detection of subsurface defects using active thermography and deep learning object detectors
dc.type	journal article
dc.identifier.doi	10.1109/TIM.2022.3169484
dc.relation.projectID	RTI2018-094849-B-I00
dc.relation.publisherversion	http://dx.doi.org/10.1109/TIM.2022.3169484
dc.rights.accessRights	open access
dc.type.hasVersion	AM

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