NYCU CSIC30014 Lab2: EEG Classification with EEGNet (87%+ accuracy, optimized hyperparameters, BCI Competition III dataset)
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Updated
Oct 30, 2025 - HTML
NYCU CSIC30014 Lab2: EEG Classification with EEGNet (87%+ accuracy, optimized hyperparameters, BCI Competition III dataset)
Motor-imagery EEG decoding with covariance alignment (EA/Riemannian) and information-maximization test-time adaptation on an EEGNet backbone — benchmarked on BCI Competition IV-2a & IV-2b (within-subject and cross-subject).
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