Dmitry Gura1,2, Bo Dong3,*, Duaa Mehiar4, Nidal Al Said5
CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1995-2014, 2024, DOI:10.32604/cmc.2024.048238
Abstract The motivation for this study is that the quality of deep fakes is constantly improving, which leads to the need to develop new methods for their detection. The proposed Customized Convolutional Neural Network method involves extracting structured data from video frames using facial landmark detection, which is then used as input to the CNN. The customized Convolutional Neural Network method is the date augmented-based CNN model to generate ‘fake data’ or ‘fake images’. This study was carried out using Python and its libraries. We used 242 films from the dataset gathered by the Deep Fake… More >
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