SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms
Author:
Affiliation:
1. CSE and IT Department of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran
2. School of Science and Technology, Nottingham Trent University, Nottingham, U.K.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation
Link
http://xplorestaging.ieee.org/ielx7/7333/9695946/09834934.pdf?arnumber=9834934
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3. Automated explainable wavelet-based sleep scoring system for a population suspected with insomnia, apnea and periodic leg movement;Medical Engineering & Physics;2024-08
4. Single-Channel EEG Classification of Human Attention with Two-Branch Multiscale CNN and Transformer Model;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
5. Clustering-based Augmentation for Effective Self-supervised Learning in Sleep Staging;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
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