Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 2198-6053

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text ; day:26 ; month:4 ; year:2022 ; pages:1-13
Complex & intelligent systems ; (26.4.2022), 1-13

Creator: Shaaban, Mai A.
Hassan, Yasser F.
Guirguis, Shawkat K.

Contributor: SpringerLink (Online service)

DOI: 10.1007/s40747-022-00741-6

URN: urn:nbn:de:101:1-2022070907113153616330

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

Last update: 15.08.2025, 7:27 AM CEST

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Shaaban, Mai A.
Hassan, Yasser F.
Guirguis, Shawkat K.
SpringerLink (Online service)

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Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text

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