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Riemannian geometry-based transfer learning for reducing training time in c-VEP BCIs
One of the main problems that a brain-computer interface (BCI) face is that a training stage is required for acquiring training data to calibrate its classification model just before every use. Transfer learning is a promising method for addressing the problem. In this paper, we propose a Riemannian...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197830/ https://www.ncbi.nlm.nih.gov/pubmed/35701505 http://dx.doi.org/10.1038/s41598-022-14026-y |