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Decoupled appearance and motion learning for efficient anomaly detection in surveillance video.

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Bibliographic Details
Title: Decoupled appearance and motion learning for efficient anomaly detection in surveillance video.
Authors: Li, Bo1, Bo.Li@UGent.be, Leroux, Sam1, Simoens, Pieter1
Source: Computer Vision & Image Understanding; Sep2021, Vol. 210, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
FullText Text:
  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 152188810
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Decoupled appearance and motion learning for efficient anomaly detection in surveillance video.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=152188810
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.cviu.2021.103249
    Languages:
      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
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      – TitleFull: Decoupled appearance and motion learning for efficient anomaly detection in surveillance video.
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            NameFull: Li, Bo
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            NameFull: Leroux, Sam
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            NameFull: Simoens, Pieter
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          Dates:
            – D: 01
              M: 09
              Text: Sep2021
              Type: published
              Y: 2021
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              Value: 210
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            – TitleFull: Computer Vision & Image Understanding
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