1. University of Kragujevac Digital Archive
  2. University of Kragujevac
  3. Faculty of Engineering, Kragujevac
Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/22893
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dc.contributor.authorGeroski, Tijana-
dc.contributor.authorPavić, Ognjen-
dc.contributor.authorDašić, Lazar-
dc.contributor.authorAmini, Amir-
dc.contributor.authorFilipovic, Nenad-
dc.date.accessioned2026-01-14T10:20:07Z-
dc.date.available2026-01-14T10:20:07Z-
dc.date.issued2025-
dc.identifier.isbn978-3-031-99200-1en_US
dc.identifier.issn2367-3370en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/22893-
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleCardiac Segmentation Using UNETR: A Transformer Based Deep Learning Approach on the ACDC Dataseten_US
dc.typeconferenceObjecten_US
dc.identifier.doi10.1007/978-3-031-99201-8_35en_US
dc.source.conferenceApplied Artificial Intelligence 4: Medicine, Biology, Chemistry, Financial, Games, Engineeringen_US
Appears in Collections:Faculty of Engineering, Kragujevac

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