Results 121 to 130 of about 8,150 (174)

Deepfake Detection

From elections, to wars, to people’s personal lives, deepfakes have become ever more present, blurring the distinction between reality and fiction. Many deep learning-based deepfake detection methods lack generalizability.
Lucas, Abem, Tong, Timothy
core   +1 more source

Spatiotemporal deep learning for real-time video-based deepfake detection using 3DCNN, 3DResNet, TCN, and VAE. [PDF]

Sci Rep
Agrawal P, Pathak D, Madaan V, Verma PK, Choo WO.   +4 more
europepmc   +1 more source

Self-supervised Deepfake detection with Local Feature Exploration

embargoed_20260417Deepfake detection remains a challenging and critical task in security. No single model excels across all types of manipulated faces. This research aims to discover the importance of different parts of the face in the deepfake detection
SOLTANDOOST NARY, ELAHE SADAT
core  

Deepfake face detection using hybrid bag-of-visual-words and multi-CNN feature fusion. [PDF]

Sci Rep
Alrahhal M, Alqahtani F, Latip R, AlShabi M, Abd-Elhafiez WM.   +4 more
europepmc   +1 more source

The Social Iowa Gambling Task: a promising tool for assessing deception detection in real-world contexts in adulthood. [PDF]

J Gerontol B Psychol Sci Soc Sci
Frei V, Lighthall NR, Faulkner R, El-Shafie D, Lin T, Ten Brinke L, Wilson RC, Ebner NC.   +7 more
europepmc   +1 more source

Stacked multi-fusion CNN: an adaptive attention model for privacy preserving deepfake forensics. [PDF]

Sci Rep
Rout J, Mishra M, Barik RC, Yadav DK, Prasad DK, Sekh AA.   +5 more
europepmc   +1 more source

Attention and residual mechanism-based CNN architecture (ARC-Net) with enhanced fairness generalization for deepfake facial image detection. [PDF]

PLoS One
Reza MS, Elias F, Mahmud MI, Ahmed N.
europepmc   +1 more source

Deepfake-teknologian vaikutus yrityksen tietoturvaan

Opinnäytetyön tarkoituksena oli tutkia deepfake-teknologian vaikutuksia yritysten tietoturvaan sekä selvittää keinoja, joilla yritykset voivat suojautua deepfake-uhkilta.
Lalli, Matilda
core  

A hybrid spatial-frequency attention-based algorithm using efficientnet for robust and interpretable deepfake detection. [PDF]

Sci Rep
Kumar M, Kumar A, Yadav V, Shankar A, Chauhan P.   +4 more
europepmc   +1 more source

Interpol review of detection of AI-generated image and video deepfakes, 2022-2025. [PDF]

Forensic Sci Int Synerg
van Lierop S, Najdenkoska I, Worring M, Geradts Z.   +3 more
europepmc   +1 more source