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Conference Paper: HR-NAS: Searching Efficient High-Resolution Neural Architectures With Lightweight Transformers

TitleHR-NAS: Searching Efficient High-Resolution Neural Architectures With Lightweight Transformers
Authors
Issue Date2021
Citation
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual Conference, 19-25 June 2021, p. 2982-2992 How to Cite?
DescriptionPaper Session Three: Paper ID 543
Persistent Identifierhttp://hdl.handle.net/10722/301431

 

DC FieldValueLanguage
dc.contributor.authorDing, M-
dc.contributor.authorLian, X-
dc.contributor.authorYang, L-
dc.contributor.authorWang, P-
dc.contributor.authorJin, X-
dc.contributor.authorLu, Z-
dc.contributor.authorLuo, P-
dc.date.accessioned2021-07-27T08:10:58Z-
dc.date.available2021-07-27T08:10:58Z-
dc.date.issued2021-
dc.identifier.citationProceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Virtual Conference, 19-25 June 2021, p. 2982-2992-
dc.identifier.urihttp://hdl.handle.net/10722/301431-
dc.descriptionPaper Session Three: Paper ID 543-
dc.languageeng-
dc.relation.ispartofIEEE Computer Vision and Pattern Recognition (CVPR) Proceedings-
dc.titleHR-NAS: Searching Efficient High-Resolution Neural Architectures With Lightweight Transformers-
dc.typeConference_Paper-
dc.identifier.emailLuo, P: pluo@hku.hk-
dc.identifier.authorityLuo, P=rp02575-
dc.identifier.hkuros323755-
dc.identifier.spage2982-
dc.identifier.epage2992-

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