About the Project - The Deepfake Detection System is an AI-driven platform developed to identify manipulated digital media, focusing on videos. It integrates deep learning model to analyze visual artifacts and motion inconsistencies. The system is deployed through a Flask-based web application, providing users with authenticity scores, visual explanations, and secure access features. Key Points : - Detects fake videos and images using deep learning - Combines temporal and frame-level analysis for video deepfake detection - Uses ResNeXt50 + LSTM for motion inconsistency analysis in videos - Applies Xception network for frame-level artifact detection - Uses EfficientNet-B0 for image authenticity classification - Built with Flask backend and HTML/CSS/JavaScript frontend - Powered by PyTorch and TensorFlow/Keras frameworks - Provides fake probability scores and heatmaps for explainability - Includes a secure user authentication system Accuracy : ~96%