Negative-Sample-Free Contrastive Self-Supervised Learning for Electroencephalogram-Based Motor Imagery Classification
Motor imagery-based brain-computer interface (MI-BCI) systems convert user intentions into computer commands, aiding the communication and rehabilitation of individuals with motor disabilities. Traditional MI classification relies on supervised learning; however, it faces challenges in acquiring lar...
| Κύριοι συγγραφείς: | , , , |
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| Μορφή: | Άρθρο |
| Γλώσσα: | English |
| Έκδοση: |
IEEE
2024-01-01
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| Σειρά: | IEEE Access |
| Θέματα: | |
| Διαθέσιμο Online: | https://ieeexplore.ieee.org/document/10680037/ |