Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture.
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| Title: | Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture. |
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| Authors: | Katı, Bekir Eray1, eraykati@sdu.edu.tr, Küçüksille, Ecir Uğur2, ecirkucuksille@sdu.edu.tr, Sarıman, Güncel3, guncelsariman@mu.edu.tr |
| Source: | Applied Sciences (2076-3417); Jan2025, Vol. 15 Issue 2, p525, 21p |
| Database: | Applied Science & Technology Source |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 182434058 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/app15020525 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 525 Titles: – TitleFull: Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Katı, Bekir Eray – PersonEntity: Name: NameFull: Küçüksille, Ecir Uğur – PersonEntity: Name: NameFull: Sarıman, Güncel IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 01 Text: Jan2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20763417 Numbering: – Type: volume Value: 15 – Type: issue Value: 2 Titles: – TitleFull: Applied Sciences (2076-3417) Type: main |
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