EEGSym: Overcoming Inter-Subject Variability in Motor Imagery Based BCIs With Deep Learning
In this study, we present a new Deep Learning (DL) architecture for Motor Imagery (MI) based Brain Computer Interfaces (BCIs) called <italic>EEGSym</italic>. Our implementation aims to improve previous state-of-the-art performances on MI classification by overcoming inter-subject variabi...
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| Main Authors: | , , , , |
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| Format: | Book |
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IEEE,
2022-01-01T00:00:00Z.
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| Online Access: | Connect to this object online. |
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |