Results 71 to 80 of about 2,785,599 (172)

Statistics-aware Audio-visual Deepfake Detector [PDF]

peer reviewedIn this paper, we propose an enhanced audio-visual deep detection method. Recent methods in audio-visual deepfake detection mostly assess the synchronization between audio and visual features.
ASTRID, Marcella, GHORBEL, Enjie, AOUADA, Djamila   +2 more
core   +1 more source

A Comparative Analysis of Compression and Transfer Learning Techniques in DeepFake Detection Models

Mathematics
DeepFake detection models play a crucial role in ambient intelligence and smart environments, where systems rely on authentic information for accurate decisions.
Andreas Karathanasis, John Violos, Ioannis Kompatsiaris   +2 more
doaj   +1 more source

GBDF: Gender Balanced DeepFake Dataset Towards Fair DeepFake Detection

, 2022
Facial forgery by deepfakes has raised severe societal concerns. Several solutions have been proposed by the vision community to effectively combat the misinformation on the internet via automated deepfake detection systems.
Rattani, Ajita, Nadimpalli, Aakash Varma
core  

Neural Network Ensemble Method for Deepfake Classification Using Golden Frame Selection

Big Data and Cognitive Computing
Deepfake technology poses significant threats in various domains, including politics, cybersecurity, and social media. This study uses the golden frame selection technique to present a neural network ensemble method for deepfake classification.
Khrystyna Lipianina-Honcharenko, Nazar Melnyk, Andriy Ivasechko, Mykola Telka, Oleg Illiashenko   +4 more
doaj   +1 more source

Face Forgery Detection and Attribution via Prototype Disentanglement [PDF]

Jisuanji kexue yu tansuo
The detection and attribution of face forgery aims to determine whether a face in an image or video has been manipulated or synthesized using Deepfake techniques, as well as to further analyze the Deepfake method behind it.
QIAN Fei, LI Wei, CHEN Peng, CHEN Haoran, XIE Lipeng, LIU Liyuan
doaj   +1 more source

FakeSound: Deepfake General Audio Detection [PDF]

With the advancement of audio generation, generative models can produce highly realistic audios. However, the proliferation of deepfake general audio can pose negative consequences.
Xie, Zeyu, Wu, Mengyue, Li, Baihan, Liang, Zheng, Yu, Kai, Xu, Xuenan   +5 more
core   +1 more source

An Investigation into the Utilisation of CNN with LSTM for Video Deepfake Detection

Applied Sciences
Video deepfake detection has emerged as a critical field within the broader domain of digital technologies driven by the rapid proliferation of AI-generated media and the increasing threat of its misuse for deception and misinformation.
Sarah Tipper, Hany F. Atlam, Harjinder Singh Lallie   +2 more
doaj   +1 more source

Privacy-preserving DeepFake face image detection [PDF]

All the existing models for DeepFake detection focus on plaintext faces. However, outsourced computing is usually considered in practical applications for DeepFake detection and the input data may contain private and sensitive information.
Zhao, Guoying, Xia, Zhihua, Chen, Beijing, Liu, Xin   +3 more
core   +1 more source

Deepfake detection: critical review of state-of-the-art approaches and future perspectives

Discover Applied Sciences
In recent years, the advancement of technology, particularly in domains such as AI, machine learning, and deep learning, has fostered the development of novel tools for altering visual media, including images, audios, and videos.
B. C. Soundarya, H. L. Gururaj
doaj   +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