CwA-T combines a channelwise CNN autoencoder with a single-head transformer to detect abnormal EEG, reporting 85.0% per-case accuracy on TUH Abnormal EEG Corpus with lower compute than standalone transformers.
A comprehensive survey on the detection, classification, and challenges of neurological disorders
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CwA-T: A Channelwise AutoEncoder with Transformer for EEG Abnormality Detection
CwA-T combines a channelwise CNN autoencoder with a single-head transformer to detect abnormal EEG, reporting 85.0% per-case accuracy on TUH Abnormal EEG Corpus with lower compute than standalone transformers.