Project is mainly focused on fake news detection using several Deep Learning techniques, comparing them, and visualizing the final outputs in order to understand the semmantics that are extracted from the text.
Project is split into 4 main activities planned.
- Testing with at least 4 different techniques.
- Comparison between the models performances.
- (Maybe) Validation with other datasets.
Below links are for exsisting active work that is trying to fix the issue of false news spreading and fake vidoes detection.
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Intel's deep fake detector lab: https://www.intel.com/content/www/us/en/newsroom/news/intel-introduces-real-time-deepfake-detector.html#gs.2z7m41
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Active Kaggle challenges for Fake news detection: https://paperswithcode.com/dataset/fnc-1