Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/16837
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dc.contributor.authorSustersic, Tijana-
dc.contributor.authorGribova, Varvara-
dc.contributor.authorNikolic, Milica-
dc.contributor.authorLavale, Philip-
dc.contributor.authorVrana, Nihal Engin-
dc.date.accessioned2023-02-24T10:55:30Z-
dc.date.available2023-02-24T10:55:30Z-
dc.date.issued2022-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/16837-
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleMachine learning based prediction of layer-by-layer coating thicknessen_US
dc.typeconferenceObjecten_US
dc.relation.conferenceJoint KMM-VIN / ViCEM / ESB crossdisciplinary workshop on Biomedical and bioinspired materials and structures: a cross-disciplinary approach combining the 9th KMM-VIN Industrial Workshop Biennial ViCEM Meeting Austrian Chapter Meeting of ESBen_US
Appears in Collections:Faculty of Engineering, Kragujevac

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