amrzhd / EEG-MSCNN

This project explores the impact of Multi-Scale CNNs on the classification of EEG signals in Brain-Computer Interface (BCI) systems. By comparing the performance of two models, EEGNet and MSTANN, the study demonstrates how richer temporal feature extractions can enhance CNN models in classifying EEG signals

Date Created 2024-08-13 (about a month ago)

Commits 13 (last one about a month ago)

Stargazers 68 (6 this week)

Watchers 1 (0 this week)

Forks 0

License mit

Ranking

RepositoryStats indexes 564,918 repositories, of these amrzhd/EEG-MSCNN is ranked #367,234 (35th percentile) for total stargazers, and #521,156 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #9,121/16,265.

amrzhd/EEG-MSCNN is also tagged with popular topics, for these it's ranked: deep-learning (#5,919/8170), machine-learning (#5,590/7699), signal-processing (#146/208)

Other Information

Homepage URL: https://medium.com/@amrzhd/enhancing-eeg-based-bci-classification-with-multi-scale-cnns-a-comparative-analysis-a0712417132b

All Topics

bci eegnet bci-systems eeg-signals deep-learning machine-learning signal-processing multi-scale-features

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Recent Commit History

13 commits on the default branch (main) since jan '22

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No issues have been posted

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The only known language in this repository is Jupyter Notebook

updated: 2024-09-27 @ 11:38am, id: 842157710 / R_kgDOMjJOjg