MI-EEGNET: A novel convolutional neural network for motor imagery classification-Reference-Cited by-同舟云学术

MI-EEGNET: A novel convolutional neural network for motor imagery classification

Published:2021-04 Issue: Volume:353 Page:109037
ISSN:0165-0270
Container-title:Journal of Neuroscience Methods
language:en
Short-container-title:Journal of Neuroscience Methods

Author:

Riyad Mouad,Khalil Mohammed,Adib Abdellah

Publisher

Elsevier BV

Subject

General Neuroscience

Reference49 articles.

1. Augmenting the size of EEG datasets using generative adversarial networks;Abdelfattah;in: 2018 International Joint Conference on Neural Networks (IJCNN),2018

2. Brain computer interfacing: Applications and challenges;Abdulkader;Egyptian Inform. J.,2015

3. Filter bank common spatial pattern algorithm on BCI competition IV datasets 2a and 2b;Ang;Front. Neurosci.,2012

4. Multiclass Brain–Computer interface classification by riemannian geometry;Barachant;IEEE Trans. Biomed. Eng.,2012

5. User-customized brain computer interfaces using Bayesian optimization;Bashashati;J. Neural Eng.,2016

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