vlawhern/arl-eegmodels
A collection of CNN models for EEG signal classification built with Keras and TensorFlow for brain-computer interface research.

This repository provides well-validated convolutional neural network models for EEG signal processing and classification, developed by the Army Research Laboratory. It includes EEGNet, DeepConvNet, ShallowConvNet, and SSVEP variant models implemented in Keras/TensorFlow. The models are designed to facilitate reproducible research and enable researchers to easily use and compare these architectures on their own EEG data for brain-computer interface applications.