BCI classification on Hinss inter-subject 2021
52.4Balanced AccuracyTSMNet(SPDDSMBN)
Evaluation Results
| Method | Links | |
|---|---|---|
| TSMNet(SPDDSMBN)UDA=yes, degrees of freedom=14, classes=32022.06 | 52.4 | |
| (1.5)-LCMBackbone=SPDDSMBN, Classifier=SPD MLR2023.05 | 51.65 | |
| (1)-LCMBackbone=SPDDSMBN, Classifier=SPD MLR2023.05 | 51.6 | |
| (1,0)-LEMBackbone=SPDDSMBN, Classifier=SPD MLR2023.05 | 51.41 | |
| Gyro-AIMBackbone=SPDDSMBN2023.05 | 50.65 | |
| EEGNet+DANNUDA=yes, degrees of freedom=14, classes=32022.06 | 50 | |
| LogEig MLRBackbone=SPDDSMBN2023.05 | 49.68 | |
| ShConvNet+DANNUDA=yes, degrees of freedom=14, classes=32022.06 | 48.8 | |
| FBCSP+DSS+LDAUDA=yes, degrees of freedom=14, classes=32022.06 | 48.4 | |
| URPA+MDMUDA=yes, degrees of freedom=14, classes=32022.06 | 48.4 | |
| EEGNetUDA=no, degrees of freedom=14, classes=32022.06 | 47.8 | |
| ShConvNetUDA=no, degrees of freedom=14, classes=32022.06 | 45.9 | |
| FBCSP+SVMUDA=no, degrees of freedom=14, classes=32022.06 | 45.6 | |
| FB+TSM+LRUDA=no, degrees of freedom=14, classes=32022.06 | 45.1 | |
| TSM+SVMUDA=no, degrees of freedom=14, classes=32022.06 | 41.7 | |
| SPDOT-TSM+SVMUDA=yes, degrees of freedom=14, classes=32022.06 | 40.4 |