A Deep Learning-Based Pipeline for Multi-Class Motor Imagery Problems with Small Portion of Labeled Datasets-Reference-Cited by-同舟云学术

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A Deep Learning-Based Pipeline for Multi-Class Motor Imagery Problems with Small Portion of Labeled Datasets

Published:2022-12-21 Issue: Volume: Page:
ISSN:
Container-title:2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME)
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Author:

Abdollahpour Neda¹,Yazdchi Mohammadreza¹,Baharlouei Zahra²

Affiliation:

1. Ragheb Isfahani Institute of Higher Education,Department of Biomedical Engineering,Isfahan,Iran

2. School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences,Medical Image and Signal Processing Research Center,Isfahan,Iran

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10052788/10052797/10053052.pdf?arnumber=10053052

Reference53 articles.

1. Brain-computer interfaces based on the steady-state visual-evoked response

2. An efficient P300-based brain–computer interface for disabled subjects

3. Neurofeedback-based motor imagery training for brain–computer interface (BCI)

4. Steady-State VEP-Based Brain-Computer Interface Control in an Immersive 3D Gaming Environment

5. BCI Competition 2008-Graz data set A. Institute for Knowledge Discovery (Laboratory of Brain-Computer Interfaces);brunner;Graz University of Technology,2008

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