Results 201 to 210 of about 815 (250)

A high-performance adaptive fusion network for face anti-spoofing detection. [PDF]

Sci Rep
Qi H, Han R, Duan K, Shi Y, Qi X, Gao C, Ren L.   +6 more
europepmc   +1 more source

Blockchain Technology as a Catalyst for Business Model Transformation and Organizational Change: Insights From Finnish Case Studies

Strategic Change, EarlyView.
ABSTRACT Blockchain technology entails more than new operational tools; it is a strategic decision‐making challenge that reshapes how organizations create, deliver, and capture value. This research uses a multiple‐case study approach in the Finnish context, conducting 11 semi‐structured interviews.
Melisa Petra Benchis, Khuram Shahzad, Sorin Dan, Syed Hammad Ul Haq   +3 more
wiley   +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 video deception detection using visual attention-based method. [PDF]

Sci Rep
Lal K, Shiwani S, Gandhi GC.
europepmc   +1 more source

CFDMI-SEC: An optimal model for copy-move forgery detection of medical image using SIFT, EOM and CHM. [PDF]

PLoS One
Amiri E, Mosallanejad A, Sheikhahmadi A.
europepmc   +1 more source

BAAR: A framework for blockchain-based anonymous and revocable user authentication scheme. [PDF]

PLoS One
Ahmed M, Ahmad A, Zeshan F, Akram S.
europepmc   +1 more source

Securing Cyber-Physical Water Infrastructures: A Hybrid Intrusion Detection System for IoT Telemetry and Industrial Protocols. [PDF]

Sensors (Basel)
López Rodríguez C, Ortega Velázquez MÁ, Jara AJ.   +2 more
europepmc   +1 more source

Decoding deception: state-of-the-art approaches to deep fake detection. [PDF]

Front Big Data
Hussain T, Reddy BT, Phanindra K, Terumalasetti S, Khan GA.   +4 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Revisiting face forgery detection towards generalization

Neural Networks
Face forgery detection aims to distinguish AI generated fake faces with real faces. With the rapid development of face forgery creation algorithms, a large number of generative models have been proposed, which gradually reduce the local distortion phenomenon or the specific frequency traces in these models. At the same time, in the process of face data
Nannan Wang, Decheng Liu, Xb Gao
exaly   +3 more sources

Improving Generalization by Commonality Learning in Face Forgery Detection

IEEE Transactions on Information Forensics and Security, 2022
Zhihua Xia, Jianwei Fei, Zhili Zhou
exaly   +2 more sources