Fangyao Shen

Self-Supervised Learning for Sleep Stage Classification with Temporal Augmentation and False Negative Suppression

Self-supervised learning has been gaining attention in the field of sleep stage classification. It learns representations with unlabeled electroencephalography (EEG) signals, which alleviates the cost of labeling for specialists. However, most self-supervised approaches assume only the two augmented…