EEGNet
Tool: EEGNet
Site: https://github.com/vlawhern/arl-eegmodels
Authors: Vernon Lawhern (ARL)
Software Language(s): Python, Tensorflow
Software Type: Machine Learning Model Definitions, Visualization Tools
What it does:
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Provides tools for training and visualization of learned features from Compact Convolutional Neural Networks (CNNs) for EEG-based Brain-Computer Interfaces (BCI). |
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Implementation of EEGNet, a compact CNN for neural decoding that generalizes across paradigms better than, and achieves comparably high performance to, the state-of-the-art BCI algorithms. |
Why is this important?
Cross-subject, cross-task BCI decoders that require little or no calibration are essential for any real-world application of non-invasive neurotechnology. |
Principal publication:
Lawhern, V. J., Solon, A. J., Waytowich, N. R., Gordon, S. M., Hung, C. P., & Lance, B. J. (2018). EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces. Journal of neural engineering, 15(5), 056013. |