| dc.contributor.author | Durrant, Aiden | |
| dc.contributor.author | Leontidis, Georgios | |
| dc.date.accessioned | 2022-07-08T14:06:00Z | |
| dc.date.available | 2022-07-08T14:06:00Z | |
| dc.date.issued | 2022-07-01 | |
| dc.identifier | 215675684 | |
| dc.identifier | 4fcbd722-31b4-4948-8324-6e908132efe2 | |
| dc.identifier | 85133280465 | |
| dc.identifier.citation | Durrant , A & Leontidis , G 2022 , ' Hyperspherically Regularized Networks for Self-Supervision ' , Image and Vision Computing , vol. 124 , 104494 . https://doi.org/10.1016/j.imavis.2022.104494 | en |
| dc.identifier.issn | 0262-8856 | |
| dc.identifier.other | ORCID: /0000-0001-6671-5568/work/115777853 | |
| dc.identifier.other | ORCID: /0000-0002-8375-4523/work/148047427 | |
| dc.identifier.uri | https://hdl.handle.net/2164/18828 | |
| dc.description | Acknowledgments 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 Agreement | en |
| dc.format.extent | 338787 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Image and Vision Computing | en |
| dc.subject | SDG 9 - Industry, Innovation, and Infrastructure | en |
| dc.subject | 2040 Data and Artificial Intelligence | en |
| dc.subject | Self-supervised learning | en |
| dc.subject | Representation learning | en |
| dc.subject | Representation separability | en |
| dc.subject | Image classification | en |
| dc.subject | QA75 Electronic computers. Computer science | en |
| dc.subject | Supplementary Data | en |
| dc.subject.lcc | QA75 | en |
| dc.title | Hyperspherically Regularized Networks for Self-Supervision | en |
| dc.type | Journal article | en |
| dc.contributor.institution | University of Aberdeen.Computing Science | en |
| dc.contributor.institution | University of Aberdeen.Vice Principals | en |
| dc.contributor.institution | University of Aberdeen.Machine Learning | en |
| dc.description.status | Peer reviewed | en |
| dc.identifier.doi | https://doi.org/10.1016/j.imavis.2022.104494 | |
| dc.identifier.vol | 124 | en |
