Exploring Convolutional Recurrent architectures for anomaly detection in videos: a comparative study

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 2731-0809

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Exploring Convolutional Recurrent architectures for anomaly detection in videos: a comparative study ; volume:1 ; number:1 ; day:22 ; month:9 ; year:2021 ; pages:1-16 ; date:12.2021
Discover artificial intelligence ; 1, Heft 1 (22.9.2021), 1-16, 12.2021

Creator: Ravi, Ambareesh
Karray, Fakhri

Contributor: SpringerLink (Online service)

DOI: 10.1007/s44163-021-00004-2

URN: urn:nbn:de:101:1-2021112820160957551597

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:30 AM CEST

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Ravi, Ambareesh
Karray, Fakhri
SpringerLink (Online service)

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Exploring Convolutional Recurrent architectures for anomaly detection in videos: a comparative study

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