HacktivSpace/multidisciplinary-deepfake-detection

A solution for deepfake detection across multiple modalities, including images, audio, and video, using ML models like CNNs, Transformers, SVMs, Bayesian networks, and Vision Transformers. This repository includes data preprocessing, model training, evaluation scripts, and Docker support for deployment.

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This solution helps analysts, journalists, and content moderators identify fabricated or manipulated content. It takes images, audio, or video files as input and uses various machine learning techniques to determine if the content is real or a deepfake. The output is a clear classification indicating whether the content is authentic or artificially generated, helping users distinguish genuine media from fakes.

No commits in the last 6 months.

Use this if you need to reliably detect deepfakes across different types of media like photos, spoken audio, and video clips.

Not ideal if you are looking for a simple, plug-and-play web tool and do not have technical expertise in running scripts or using Docker.

deepfake-detection media-verification content-moderation digital-forensics fake-news-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

13

Forks

3

Language

Python

License

Last pushed

Aug 18, 2024

Commits (30d)

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