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

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

Open source

DOI: 10.1007/s40747-022-00741-6
Published: 2022-04-26
Container: Complex & Intelligent Systems
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s40747-022-00741-6,
  title = {Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text},
  author = {Mai A. Shaaban and Yasser F. Hassan and Shawkat K. Guirguis},
  year = {2022},
  journal = {Complex \&amp; Intelligent Systems},
  doi = {10.1007/s40747-022-00741-6},
  url = {https://doi.org/10.1007/s40747-022-00741-6}
}

RIS

TY  - JOUR
TI  - Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text
AU  - Mai A. Shaaban
AU  - Yasser F. Hassan
AU  - Shawkat K. Guirguis
PY  - 2022
JO  - Complex &amp; Intelligent Systems
DO  - 10.1007/s40747-022-00741-6
UR  - https://doi.org/10.1007/s40747-022-00741-6
ER  -

APA

Shaaban, M. A., Hassan, Y. F., & Guirguis, S. K. (2022). Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text. Complex & Intelligent Systems. https://doi.org/10.1007/s40747-022-00741-6

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crossref · retrieved 2026-09-26T08:34:01.365Z