vlawhern / arl-eegmodels

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

Date Created 2018-05-16 (6 years ago)

Commits 34 (last one 2 years ago)

Stargazers 1,245 (1 this week)

Watchers 41 (0 this week)

Forks 305

License other

Ranking

RepositoryStats indexes 622,366 repositories, of these vlawhern/arl-eegmodels is ranked #43,167 (93rd percentile) for total stargazers, and #52,625 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #6,841/126,222.

vlawhern/arl-eegmodels is also tagged with popular topics, for these it's ranked: deep-learning (#1,130/8741), tensorflow (#379/2290), keras (#115/806), convolutional-neural-networks (#58/561), eeg (#5/136)

Other Information

vlawhern/arl-eegmodels has 1 open pull request on Github, 3 pull requests have been merged over the lifetime of the repository.

Github issues are enabled, there are 13 open issues and 29 closed issues.

All Topics

eeg keras tensorflow deep-learning eeg-classification sensory-motor-rhythm brain-computer-interface event-related-potentials time-series-classification convolutional-neural-networks

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1 commits on the default branch (master) since jan '22

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The only known language in this repository is Python

updated: 2025-03-02 @ 10:44pm, id: 133590348 / R_kgDOB_ZtTA