EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces

Abstract

Our results suggest that EEGNet is robust enough to learn a wide variety of interpretable features over a range of BCI tasks. Our models can be found at: https://github.com/vlawhern/arl-eegmodels.

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Publication Info

Year: 2018
Type: article
Volume: 15
Issue: 5
Pages: 056013-056013
Citations: 3477
Access: Closed

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APA Style

                            
                                
                                    Vernon J. Lawhern, 
                                
                                    Amelia J. Solon, 
                                
                                    Nicholas R. Waytowich
                                
                                et al.
                            
                            (2018). 
                            EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces. 
                            Journal of Neural Engineering
                            , 15
                            (5)
                            , 056013-056013.
                            https://doi.org/10.1088/1741-2552/aace8c
                        

Identifiers

DOI: 10.1088/1741-2552/aace8c