2D spatiotemporal convolutions reduce training time on high-dimensional EEG data while maintaining performance and creating distinct representational geometries compared with concatenated 1D convolutions.
Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset,
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Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Nets
2D spatiotemporal convolutions reduce training time on high-dimensional EEG data while maintaining performance and creating distinct representational geometries compared with concatenated 1D convolutions.