My project focuses on detecting deepfake images using machine learning techniques. It analyzes facial features, lighting inconsistencies, and pixel-level anomalies to differentiate between real and AI-generated visuals. By training models on datasets containing both authentic and manipulated images, the system learns to identify subtle signs of tampering. This project aims to combat the growing threat of deepfakes by providing a reliable tool for verifying image authenticity, which can be useful in media, security, and digital forensics.
Deep Fake Detection System
A machine learning project that detects deepfake images by analyzing facial features and inconsistencies to distinguish real from AI-generated visuals.
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