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Automated surface defect detection in metals: a comparative review of object detection and semantic segmentation using deep learning

dc.contributor.authorUsamentiaga Fernández, Rubén 
dc.contributor.authorGonzález Lema, Darío 
dc.contributor.authorDíaz Pedrayes, Óscar 
dc.contributor.authorGarcía Martínez, Daniel Fernando 
dc.date.accessioned2022-09-06T07:28:27Z
dc.date.available2022-09-06T07:28:27Z
dc.date.issued2021
dc.identifier.isbn9781728164014
dc.identifier.issn0197-2618
dc.identifier.urihttp://hdl.handle.net/10651/64510
dc.descriptionIEEE Industry Applications Society Annual Meeting (IAS) (56th. 2021. Virtual)
dc.description.sponsorshipThis work has been partially funded by the project RTI2018-094849-B-I00 of the Spanish National Plan for Research, Development and Innovation.
dc.language.isoeng
dc.relation.ispartofConference record - ias annual meeting (IEEE industry applications society)
dc.rights© IEEE
dc.rightsCC Reconocimiento – No Comercial – Sin Obra Derivada 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85124693019&doi=10.1109%2fIAS48185.2021.9677231&partnerID=40&md5=5bb114798ea17463d7a48d09ae18ed2f
dc.titleAutomated surface defect detection in metals: a comparative review of object detection and semantic segmentation using deep learning
dc.typeconference outputspa
dc.identifier.doi10.1109/IAS48185.2021.9677231
dc.relation.projectIDRTI2018-094849-B-I00
dc.relation.publisherversionhttp://dx.doi.org/10.1109/IAS48185.2021.9677231
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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