Optimizing EEG-Based Sleep Staging: Adversarial Deep Learning Joint Domain Adaptation

Optimizing EEG-Based Sleep Staging: Adversarial Deep Learning Joint Domain Adaptation

Sleep-stage classification is a critical aspect of understanding sleep patterns in sleep research and healthcare. However, challenges arise when dealing with a limited number of labeled samples in the target domain. Traditional methods in Deep Learning (DL) and Domain Adaptation (DA) globally compar...

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Bibliographic Details
Main Authors: Roya Ghasemigarjan, Mohammad Mikaeili, Seyed Kamaledin Setarehdan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Adversarial learning
channel optimization
classification accuracy
deep learning
domain adaptation
EEG signal
Online Access:https://ieeexplore.ieee.org/document/10597569/
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