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dc.contributor.authorDurrant, Aiden
dc.contributor.authorLeontidis, Georgios
dc.date.accessioned2022-07-08T14:06:00Z
dc.date.available2022-07-08T14:06:00Z
dc.date.issued2022-07-01
dc.identifier.citationDurrant , A & Leontidis , G 2022 , ' Hyperspherically Regularized Networks for Self-Supervision ' , Image and Vision Computing , vol. 124 , 104494 . https://doi.org/10.1016/j.imavis.2022.104494en
dc.identifier.issn0262-8856
dc.identifier.otherPURE: 215675684
dc.identifier.otherPURE UUID: 4fcbd722-31b4-4948-8324-6e908132efe2
dc.identifier.otherORCID: /0000-0001-6671-5568/work/115777853
dc.identifier.otherScopus: 85133280465
dc.identifier.urihttps://hdl.handle.net/2164/18828
dc.descriptionAcknowledgments This work used the Cirrus UK National Tier-2 HPC Service at EPCC (http://www.cirrus.ac.uk). Access granted through the project: ec173 - Next gen self-supervised learn- ing systems for vision tasks. Open access via Elsevier Agreementen
dc.language.isoeng
dc.relation.ispartofImage and Vision Computingen
dc.subjectSDG 9 - Industry, Innovation, and Infrastructureen
dc.subject2040 Data and Artificial Intelligenceen
dc.subjectSelf-supervised learningen
dc.subjectRepresentation learningen
dc.subjectRepresentation separabilityen
dc.subjectImage classificationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectSupplementary Dataen
dc.subject.lccQA75en
dc.titleHyperspherically Regularized Networks for Self-Supervisionen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Vice Principalsen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen
dc.identifier.doihttps://doi.org/10.1016/j.imavis.2022.104494


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