A hybrid transfer learning approach for multi-class classification of medical deepfakes generated by GAN and diffusion models
Abstract Artificial intelligence and deepfake technologies have enabled the rapid generation of synthetic text, images, audio, and video, creating significant challenges in detecting fraudulent content. In healthcare, fake medical data can compromise patient safety, cause misdiagnoses, and erode tru...
Збережено в:
| Автори: | , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
Springer
2026-04-01
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| Серія: | Discover Computing |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1007/s10791-026-10116-x |
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