Genetic algorithm based deep learning model adaptation for improvising the motor imagery classification
Deep learning methods have proved a promising performance for electroencephalography-based brain-computer interfaces (EEG-BCI). It is particularly encouraging that a subject-independent model can be trained using a large amount of other subjects’ data. Transfer learning methods such as adaptation or...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/179921 |