Imagined Speech Classification on BCI Competition III dataset 2020 (test)
0.8013AccuracyCNN-SNN
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CNN-SNNArchitecture=CNN-SNN2026.07 | 0.8013 | — | |
| Ko et al.Architecture=Spectro-Spatio-Temporal CNN2026.07 | 0.7019 | — | |
| Li et al.Architecture=Self-attention Module + Transfer Learning2026.07 | 0.69 | — | |
| Rousis et al.Architecture=EEGNet-SPDNet2026.07 | 0.6693 | — | |
| Zheng et al.Architecture=Statistical Features + Random Forest2026.07 | 0.5851 | — | |
| Lee et al.Architecture=Spectral Entropy + Siamese Neural Network + KNN2026.07 | 0.481 | — |