Research on unsupervised anomaly data detection method based on improved automatic encoder and Gaussian mixture model
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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2192-113X
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Research on unsupervised anomaly data detection method based on improved automatic encoder and Gaussian mixture model ; volume:11 ; number:1 ; day:29 ; month:9 ; year:2022 ; pages:1-16 ; date:12.2022
Journal of Cloud Computing ; 11, Heft 1 (29.9.2022), 1-16, 12.2022
- Urheber
-
Liu, Xiangyu
Zhu, Shibing
Yang, Fan
Liang, Shengjun
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13677-022-00328-z
- URN
-
urn:nbn:de:101:1-2022121709032158475047
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:31 MESZ
Datenpartner
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Beteiligte
- Liu, Xiangyu
- Zhu, Shibing
- Yang, Fan
- Liang, Shengjun
- SpringerLink (Online service)
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