MCGAN-a cutting edge approach to real time investigate of multimedia deepfake multi collaboration of deep generative adversarial networks with transfer learning. [PDF]
Sci RepKarim S +5 more
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The public mental representations of deepfake technology: An in-depth qualitative exploration through Quora text data analysis. [PDF]
PLoS OneCaci B +10 more
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Editorial: Interdisciplinary approaches to complex systems: highlights from FRCCS 2023/24. [PDF]
Front Big DataInterdonato R, Cherifi H.
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Steganography beyond space-time with chain of multimodal AI. [PDF]
Sci RepChang CC, Echizen I.
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Enhancing practicality and efficiency of deepfake detection. [PDF]
Sci RepBalafrej I, Dahmane M.
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Exposing Face Manipulation Based on Generative Adversarial Network-Transformer and Fake Frequency Noise Traces. [PDF]
Sensors (Basel)Man Q, Cho YI.
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Post-variational classical quantum transfer learning for binary classification. [PDF]
Sci RepYogaraj K +4 more
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Seeing is Believing: The Continued Influence of Known AI-Generated ‘Deepfake’ Videos
Clark S, Lewandowsky S.
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Die Wirklichkeit, also das tatsächliche Gefüge der Welt und des Weltalls, ist für den Menschen nur sehr eingeschränkt erfahrbar. Die menschlichen Sinne sind begrenzt, ein Hund hört viel besser als wir und unser Auge nimmt nur bestimmte Spektren des Lichts wahr. Physisch sind wir – noch – an die Erde gebunden.
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Machine-learning has enabled the creation of "deepfake videos"; highly-realistic footage that features a person saying or doing something they never did. In recent years, this technology has become more widespread and various apps now allow an average social-media user to create a deepfake video which can be shared online.
Gillian Murphy, Emma Flynn
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