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Conference Paper: Everest: A Top-K Deep Video Analytics System

TitleEverest: A Top-K Deep Video Analytics System
Authors
Lai, ZLiu, CHan, CZhang, PLo, EKao, CM
Issue Date2022
PublisherACM.
Citation
Proceedings of the 2022 International Conference on Management of Data (SIGMOD 2022), p. 2357-2360 How to Cite?
DOI: http://dx.doi.org/10.1145/3514221.3520151
Persistent Identifierhttp://hdl.handle.net/10722/319371
ISBN
9781450392495
ISI Accession Number ID
WOS:000852705400170

 

DC FieldValueLanguage
dc.contributor.authorLai, Z-
dc.contributor.authorLiu, C-
dc.contributor.authorHan, C-
dc.contributor.authorZhang, P-
dc.contributor.authorLo, E-
dc.contributor.authorKao, CM-
dc.date.accessioned2022-10-14T05:12:06Z-
dc.date.available2022-10-14T05:12:06Z-
dc.date.issued2022-
dc.identifier.citationProceedings of the 2022 International Conference on Management of Data (SIGMOD 2022), p. 2357-2360-
dc.identifier.isbn9781450392495-
dc.identifier.urihttp://hdl.handle.net/10722/319371-
dc.languageeng-
dc.publisherACM. -
dc.relation.ispartofProceedings of the 2022 International Conference on Management of Data (SIGMOD 2022)-
dc.titleEverest: A Top-K Deep Video Analytics System-
dc.typeConference_Paper-
dc.identifier.emailKao, CM: kao@cs.hku.hk-
dc.identifier.authorityKao, CM=rp00123-
dc.identifier.doi10.1145/3514221.3520151-
dc.identifier.hkuros339428-
dc.identifier.spage2357-
dc.identifier.epage2360-
dc.identifier.isiWOS:000852705400170-
dc.publisher.placeNew York, NY, USA-

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