BENDR: Using Transformers and a Contrastive Self-Supervised Learning Task to Learn From Massive Amounts of EEG Data

Deep neural networks (DNNs) used for brain–computer interface (BCI) classification are commonly expected to learn general features when trained across a variety of contexts, such that these features could be fine-tuned to specific contexts. While some success is found in such an approach, we suggest...

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Bibliographic Details

Published in:	Frontiers in human neuroscience Vol. 15; p. 653659
Main Authors:	Kostas, Demetres, Aroca-Ouellette, Stéphane, Rudzicz, Frank
Format:	Journal Article
Language:	English
Published:	Frontiers Media S.A 23.06.2021
Subjects:	brain computer interface contrastive learning convolutional neural network deep learning - artificial neural network Human Neuroscience semi-supervised learning transformers
ISSN:	1662-5161, 1662-5161
Online Access:	Get full text
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