Deep Classifiers and Wavelet Transformation for Fake Image Detection

• Autorzy: Osowski Stanislaw , Golgowski Maciej

Identyfikatory

DOI

10.26636/jtit.2023.4.1336

• Języki publikacji: EN

Abstrakty

EN

The paper presents a computer system for detecting deep fake images in videos. The system is based on continuous wavelet transformation combined with a set of classifiers composed of a few convolutional neural networks of diversified architectures. Three different forms of forged images taken from the FaceForensics++ database are considered in numerical experiments. The results of experiments involving the proposed system have shown good performance in comparison to other current approaches to this particular problem.

Słowa kluczowe

EN

continuous wavelet transform; convolutional neural; networks; deep fake; ensemble of classifiers

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2023
• Tom: nr 4
• Strony: 1--8
• Opis fizyczny: Bibliogr. 23 poz., rys., tab., wykr.

Twórcy

autor

Osowski Stanislaw

• Institute of Theory of Electrical Engineering, Measurement, and Information Systems Military University of Technology, Warsaw, Poland
• Warsaw University of Technology, Warsaw, Poland

• https://orcid.org/0000-0003-3194-4656

autor

Golgowski Maciej

• Electronic Faculty, Institute of Electronic Systems Military University of Technology, Warsaw, Poland

Bibliografia

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