A deep learning-powered system for detecting deepfake videos using a ResNeXt + LSTM hybrid model with a Django web interface for real-time predictions.

This tool uses multiple detection methods to identify AI-generated images and videos

A deep learning-based web application to automatically detect whether a given video is real or AI-generated (deepfake). This system uses ResNeXt CNN for spatial feature extraction and LSTM RNN for temporal sequence analysis, integrated with a Django web app for easy usage.

This repository contains a Deep Fake Detection model that uses Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to analyze videos and detect deepfake content. The model extracts frames from videos, processes them using deep learning techniques, and determines whether the video is real or fake based on trained data.

Automating YouTube Clickbait Detection using sentiment analysis, metadata, and thumbnails to classify video content effectively

This repository contains a Streamlit-based application for finding the video is fake or not fake