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dc.contributor.authorThota, Mamatha
dc.contributor.authorLeontidis, Georgios
dc.date.accessioned2021-06-13T21:32:01Z
dc.date.available2021-06-13T21:32:01Z
dc.date.issued2021-06-12
dc.identifier.citationThota , M & Leontidis , G 2021 , Contrastive Domain Adaptation . in Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops . Computer Vision Foundation (CVF) , pp. 1-10 . < https://openaccess.thecvf.com/content/CVPR2021W/WiCV/papers/Thota_Contrastive_Domain_Adaptation_CVPRW_2021_paper.pdf >en
dc.identifier.otherPURE: 191729965
dc.identifier.otherPURE UUID: 2b457cb5-a793-48db-90df-534fba524422
dc.identifier.otherORCID: /0000-0001-6671-5568/work/95579379
dc.identifier.otherSCOPUS: 85116068906
dc.identifier.urihttps://hdl.handle.net/2164/16665
dc.descriptionAUTHOR ONLINE USE Personal Servers. Authors and/or their employers shall have the right to post the accepted version of IEEE-copyrighted articles on their own personal servers or the servers of their institutions or employers without permission from IEEE, provided that the posted version includes a prominently displayed IEEE copyright notice and, when published, a full citation to the original IEEE publication, including a link to the article abstract in IEEE Xplore. Authors shall not post the final, published versions of their papers."en
dc.format.extent10
dc.language.isoeng
dc.publisherComputer Vision Foundation (CVF)
dc.relation.ispartofProceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshopsen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titleContrastive Domain Adaptationen
dc.typeConference itemen
dc.contributor.institutionUniversity of Aberdeen.Vice Principalsen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Centre for Energy Transitionen
dc.description.versionPublisher PDFen
dc.identifier.urlhttps://openaccess.thecvf.com/content/CVPR2021W/WiCV/papers/Thota_Contrastive_Domain_Adaptation_CVPRW_2021_paper.pdfen


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