Deepfake Detection and Reconstruction of the Original Image
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Abstract
This study takes a novel method to addressing the problems faced by false faces created by adversarial networks. The system includes a Fake Face Identification Module and a Generative Image Reconstruction Module that use deep learning techniques. The former correctly recognises falsely manufactured faces, but the latter reconstructs the original images associated with the discovered forgeries. . The procedure entails training advanced deep neural networks on a variety of datasets in order to ensure flexibility against evolving adversarial tactics. The technology improves biometric security, data integrity, and the trustworthiness of facial recognition systems by cross-referencing and recovering legitimate photos in datasets. Identity verification, surveillance, and the preservation of accurate facial picture databases are all potential applications for this project
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