Deep Fake Face Detection Using Advanced R-CNN Architectures

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.