Henrywang621/DL-based-MI-EEG-models
This code repository collects the source code of the representative deep learning-based MI-EEG models and runs a leaderboard to fairly compare these models.
This project helps neuroscientists and BCI researchers evaluate and compare different deep learning models for classifying motor imagery (MI) EEG signals. It takes raw or preprocessed MI-EEG datasets as input and outputs performance metrics and a leaderboard comparing various state-of-the-art models. Researchers can quickly benchmark their proposed models against existing solutions.
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Use this if you are a researcher in neuroscience or brain-computer interfaces (BCI) and need a standardized way to compare the performance of deep learning models on motor imagery EEG classification tasks.
Not ideal if you are looking for a plug-and-play solution for real-time BCI applications or if you are not comfortable working with command-line scripts for model evaluation.
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Language
Python
License
MIT
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Last pushed
Apr 22, 2025
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