Publication:

GenConViT: Deepfake Video Detection Using Generative Convolutional Vision Transformer

Date

2025
Journal article
https://doi.org/10.3390/app15126622
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dc.contributor.authorDeressa, Deressa Wodajo
dc.contributor.authorMareen, Hannes
dc.contributor.authorLambert, Peter
dc.contributor.authorAtnafu, Solomon
dc.contributor.authorAkhtar, Zahid
dc.contributor.authorVan Wallendael, Glenn
dc.contributor.imecauthorDeressa, Deressa Wodajo
dc.contributor.imecauthorMareen, Hannes
dc.contributor.imecauthorLambert, Peter
dc.contributor.imecauthorVan Wallendael, Glenn
dc.contributor.orcidimecMareen, Hannes::0000-0002-0660-3190
dc.contributor.orcidimecLambert, Peter::0000-0001-5313-4158
dc.contributor.orcidimecVan Wallendael, Glenn::0000-0001-9530-3466
dc.date.accessioned2025-06-30T10:32:09Z
dc.date.available2025-06-30T03:57:08Z
dc.date.available2025-06-30T10:32:09Z
dc.date.issued2025
dc.description.wosFundingTextThis research was funded by Addis Ababa University Research Grant for the Adaptive Problem-Solving Research. Reference number RD/PY-183/2021. Grant number AR/048/2021, and the Research Foundation-Flanders (FWO under project grant G0A2523N), the Flemish government (COM-PRESS project, within the relanceplan Vlaamse Veerkracht), IDLab (Ghent University-imec), Flanders Innovation and Entrepreneurship (VLAIO), and the European Union.
dc.identifier.doi10.3390/app15126622
dc.identifier.issn2076-3417
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/45865
dc.publisherMDPI
dc.source.beginpage1
dc.source.endpage21
dc.source.issue12
dc.source.journalAPPLIED SCIENCES-BASEL
dc.source.numberofpages21
dc.source.volume15
dc.title

GenConViT: Deepfake Video Detection Using Generative Convolutional Vision Transformer

dc.typeJournal article
dspace.entity.typePublication
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