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https://github.com/rishic3/generateeeg
Two Conditional GAN frameworks to perform synthetic EEG generation for dataset augmentation.
https://github.com/rishic3/generateeeg
deep-learning eeg gan
Last synced: 8 days ago
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Two Conditional GAN frameworks to perform synthetic EEG generation for dataset augmentation.
- Host: GitHub
- URL: https://github.com/rishic3/generateeeg
- Owner: rishic3
- Created: 2023-04-27T17:39:23.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-05T13:49:57.000Z (8 months ago)
- Last Synced: 2024-05-05T14:24:03.932Z (8 months ago)
- Topics: deep-learning, eeg, gan
- Language: Jupyter Notebook
- Homepage:
- Size: 7.32 MB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# GenerateEEG
Conditional GAN frameworks to perform synthetic EEG generation for dataset augmentation as 1-D signals or 2-D spectrograms.
Contains the code implementation for [GenerateEEG paper](https://github.com/rishic3/GenerateEEG/blob/main/RTM_Final_Paper.pdf).
Developed for AS.050.337: Reading the Mind: Computational Cognitive Neuroscience of Vision, Johns Hopkins University.
Authored by Rishi Chandra, [email protected]