Results 81 to 90 of about 2,785,599 (172)

Boosting Deepfake Detection Generalizability via Expansive Learning and Confidence Judgement

As deepfake technology poses severe threats to information security, significant efforts have been devoted to deepfake detection. To enable model generalization for detecting new types of deepfakes, it is required that the existing models should learn ...
Hou, Z, Zhang, LY, Hua, Z, Zheng, Y, Zhang, K   +4 more
core   +1 more source

Penerapan ResNeXt dan Long Short-Term Memory untuk Deteksi Video Deepfake

JISKA (Jurnal Informatika Sunan Kalijaga)
Deepfake is a form of facial manipulation in videos that utilizes artificial intelligence-based models to generate highly realistic visual content. The increasing spread of Deepfake has the potential to cause misinformation, manipulate public opinion ...
Chalifa Chazar, Firhan Hafiansyah, Milda Gustiana Husada, Uung Ungkawa, Rizka Milandga Milenio   +4 more
doaj   +1 more source

Robust Sequential DeepFake Detection [PDF]

Since photorealistic faces can be readily generated by facial manipulation technologies nowadays, potential malicious abuse of these technologies has drawn great concerns. Numerous deepfake detection methods are thus proposed.
Wu, Tianxing, Shao, Rui, Liu, Ziwei
core   +1 more source

DEEPFAKE CLI: Accelerated Deepfake Detection using FPGAs

, 2022
Because of the availability of larger datasets and recent improvements in the generative model, more realistic Deepfake videos are being produced each day.
Bhilare, Omkar, Singh, Rahul, Kazi, Faruk, Paranjape, Vedant, Chittupalli, Sravan, Suratkar, Shraddha   +5 more
core  

Real time detection of deepfakes using the efficient Swin attention network with global and local facial features

Discover Artificial Intelligence
The rapid advancement of deepfake generation techniques has exposed critical limitations in existing deepfake detection methods, particularly their inability to simultaneously achieve high detection accuracy and real-time efficiency across diverse ...
Muhammad Javed, Dezhi Han, Fida Hussain Dahri, Teerath Kumar, Jameel Ahmed Bhutto, Ashfaque Khowaja   +5 more
doaj   +1 more source

Human Performance in Deepfake Detection: A Systematic Review

Human Behavior and Emerging Technologies
Deepfakes refer to a wide range of computer-generated synthetic media, in which a person’s appearance or likeness is altered to resemble that of another.
Klaire Somoray, Dan J. Miller, Mary Holmes   +2 more
doaj   +1 more source

Ensemble-Based Biometric Verification: Defending Against Multi-Strategy Deepfake Image Generation

Computers
Deepfake images, synthetic images created using digital software, continue to present a serious threat to online platforms. This is especially relevant for biometric verification systems, as deepfakes that attempt to bypass such measures increase the ...
Hilary Zen, Rohan Wagh, Miguel Wanderley, Gustavo Bicalho, Rachel Park, Megan Sun, Rafael Palacios, Lucas Carvalho, Guilherme Rinaldo, Amar Gupta   +9 more
doaj   +1 more source

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

Speech DF Arena: A Leaderboard for Speech DeepFake Detection Models

IEEE Open Journal of Signal Processing
Parallel to the development of advanced deepfake audio generation, audio deepfake detection has also seen significant progress. However, a standardized and comprehensive benchmark is still missing. To address this, we introduce Speech DeepFake (DF) Arena,
Sandipana Dowerah, Atharva Kulkarni, Ajinkya Kulkarni, Hoan My Tran, Joonas Kalda, Artem Fedorchenko, Benoit Fauve, Damien Lolive, Tanel Alumae, Mathew Magimai.-Doss   +9 more
doaj   +1 more source

A Multifaceted Deepfake Prevention Framework Integrating Blockchain, Post-Quantum Cryptography, Hybrid Watermarking, Human Oversight, and Policy Governance

Computers
Deepfake technology, driven by advances in artificial intelligence (AI) and deep learning (DL), has become one of the foremost threats to digital trust and the authenticity of information.
Mohammad Alkhatib
doaj   +1 more source