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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Vydané v:	Frontiers in human neuroscience Ročník 15; s. 653659
Hlavní autori:	Kostas, Demetres, Aroca-Ouellette, Stéphane, Rudzicz, Frank
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Frontiers Media S.A 23.06.2021
Predmet:	brain computer interface contrastive learning convolutional neural network deep learning - artificial neural network Human Neuroscience semi-supervised learning transformers
ISSN:	1662-5161, 1662-5161
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