Deep Fake Face Detection Using Advanced R-CNN Architectures

Author(s)	Manoj Raj G, Maneesh Kumar G, Ajay Selvam K, Mahalakshmi G
Country	India
Abstract	Outstanding developments in deep learning have produced remarkably real AI-generated fake faces. The exploitation of this potent A.I. technology has a significant impact on people's life, thus new deep fake detection algorithms must be developed in order to properly build the deep fake phenomena. However, ad-hoc frequency analysis may reveal the fingerprints that Convolution Neural Network (CNN) engines left behind while building the deep artificial face. We'll make use of the Deep Convolutional neural network and, both of which have shown impressive classification abilities in artificial faces. We discussed the theoretical underpinnings of CNN's ability to identify phony faces.
Keywords	Keywords: Face Forgery Detection, Fake Face Identification, Convolutional Neural Networks (CNNs)
Field	Engineering
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-09
Cite This	Deep Fake Face Detection Using Advanced R-CNN Architectures - Manoj Raj G, Maneesh Kumar G, Ajay Selvam K, Mahalakshmi G - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3409
DOI	https://doi.org/10.71097/IJSAT.v16.i2.3409
Short DOI	https://doi.org/g9fcgn

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