dan-crdll/nn_project_dreamdiffusion
Re-implementation of the method proposed in ''DreamDiffusion: Generating High-Quality Images from Brain EEG Signals'' by Y. Bai, X. Wang et al. for Neural Network Course exam Topics
This project helps researchers and scientists transform raw brain EEG signals into high-quality visual images. By taking EEG data as input, it generates corresponding images, allowing for direct visualization of brain activity. This tool is ideal for neuroscientists, cognitive psychologists, and medical researchers studying brain-computer interfaces or dream states.
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Use this if you need to visualize brain activity directly as images from EEG signals for research or experimental purposes.
Not ideal if you are looking for a diagnostic medical tool or a real-time brain-computer interface for daily use.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Jul 10, 2024
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