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Oct, 2021
自监督EEG表征学习用于自动睡眠分期
Self-supervised EEG Representation Learning for Automatic Sleep Staging
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Chaoqi Yang, Danica Xiao, M. Brandon Westover, Jimeng Sun
TL;DR
本文介绍了一种名为ContraWR的自监督学习算法,可以用于从大量未标记的EEG数据中学习鲁棒的向量表示,用于睡眠分期任务,并且相比监督学习方法在数据标记少和噪声干扰情况下表现更好。
Abstract
Objective: In this paper, we aim to learn robust vector representations from massive unlabeled Electroencephalogram (
eeg
) signals, such that the learned representations (1) are expressive enough to replace the raw signals in the
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