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
Implements four peer-reviewed architectures (EEGNet, EEGNet-SSVEP, DeepConvNet, ShallowConvNet) with configurable channel and sample dimensions for domain-specific EEG tasks. Provides feature explainability through DeepExplain integration, enabling single-trial relevance attribution via DeepLIFT and LRP methods to interpret model decisions. Designed for reproducible research with straightforward API—instantiate a model, compile with standard Keras/TensorFlow workflows, and train on custom EEG datasets without additional preprocessing boilerplate.
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May 02, 2022
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