An Improved Deepfake Detection Approach Using Hybrid Architecture Based on EfficientNet and Vision Transformer. [PDF]
Banimelhem O, Alsharu AO.
europepmc +1 more source
Dual-domain self-supervised feature alignment via spectral-spatial representation learning for deepfake anomaly detection. [PDF]
He Y.
europepmc +1 more source
Deepfakebuster: a confidence-calibrated adaptive ensemble framework for robust Deepfake image detection. [PDF]
Patil R +4 more
europepmc +1 more source
Bioinspired Adaptive-Depth Neural Growth for Deepfake Video Forensics: An Entropy-Guided State-Space Framework. [PDF]
Hussain M, Saeed F, Aldera S.
europepmc +1 more source
Deepfake-huijaukset : vaikutukset yritysten julkisuuskuvaan [PDF]
Tässä opinnäytetyössä tutkittiin deepfake-huijauksia sekä huijausten vaikutuksia yritysten julkisuuskuvaan. Opinnäyte toteutettiin tutkimuksellisena kirjallisuuskatsauksena, jonka lähteinä käytettiin olemassa olevia tutkimuksia aiheesta.
Koivuranta, Kiia, Ventilä, Fiia-Riikka
core
Multimodal transformer-based watermarking for deepfake detection and digital media authentication: current progress, challenges, and future directions. [PDF]
Sim KS, Islam MT.
europepmc +1 more source
Towards Generalizable Deepfake Detection: An Inconsistency-Aware Vision-Language Model Tuning Approach. [PDF]
Zhang L, Peng S, Xu M, Lu T.
europepmc +1 more source
Multilayered Epistemic Disruption in AI-Driven Health Misinformation: Conceptual Framework and Viewpoint. [PDF]
Malkoç M.
europepmc +1 more source
Perceived opportunities and risks of using deepfake technology in grief treatment: a qualitative study among Dutch bereaved people and mental health care workers. [PDF]
van Oostrum JM, Akalin D, Lenferink L.
europepmc +1 more source
Ensemble learning model for deepfake audio detection using multi-feature extraction approach. [PDF]
Chaudhury P +3 more
europepmc +1 more source

