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Data Augmentation: Using Channel-Level Recombination to Improve Classification Performance for Motor Imagery EEG
The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface (BCI) system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation...
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| Udgivet i: | Front Hum Neurosci |
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| Main Authors: | , , , , , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Frontiers Media S.A.
2021
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7990774/ https://ncbi.nlm.nih.gov/pubmed/33776673 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnhum.2021.645952 |
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