Multi-Modal Dynamic Fusion with Training-Free Generalisation for Integrated Deepfake Detection

Published: 27 July 2026| Version 1 | DOI: 10.17632/4k24npx9f4.1
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This repository contains the complete implementation of the proposed machine learning framework, including data preprocessing, model construction, training, testing, and evaluation procedures. The code is organized into different modules and branches to ensure a clear and reproducible workflow. It includes scripts for dataset preparation, model training, performance evaluation, and result generation, as well as the required model configurations and trained weights. The project is designed to support transparency and reproducibility, allowing researchers to replicate the experiments by installing the required dependencies, preparing the dataset, running the training process, and evaluating the generated results. The main subject areas of this work include machine learning, artificial intelligence, deep learning, computer vision, and data science. No external funding was received for this research. The provided code and documentation offer a complete reproducibility workflow for verifying the reported results and supporting further research development.

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