Name
Title | ||
|---|---|---|
Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail |
Abstract | ||
|---|---|---|
The performance of brain-computer interfaces (BCIs) improves with the amount of available training data; the statistical distribution of this data, however, varies across subjects as well as across sessions within individual subjects, limiting the transferability of training data or trained models between them. In this article, we review current transfer learning techniques in BCIs that exploit sh... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/MCI.2015.2501545 | IEEE Computational Intelligence Magazine |
Keywords | DocType | Volume |
Training data,Brain modeling,Data models,Brain-computer interfaces,Spatial filters,Electroencephalography,Machine learning | Journal | 11 |
Issue | ISSN | Citations |
1 | 1556-603X | 32 |
PageRank | References | Authors |
1.05 | 23 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vinay Jayaram | 1 | 37 | 2.12 |
| Morteza Alamgir | 2 | 97 | 5.83 |
| yasemin altun | 3 | 2463 | 150.46 |
| Bernhard Schölkopf | 4 | 23120 | 3091.82 |
| Moritz Grosse-Wentrup | 5 | 273 | 24.44 |