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NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep
  Stage Classification Using Single-Channel EEG

NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG

10 April 2024
Cheol-Hui Lee
Hakseung Kim
Hyun-jee Han
Min-Kyung Jung
Byung C. Yoon
Dong-Joo Kim
ArXivPDFHTML

Papers citing "NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG"

4 / 4 papers shown
Title
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework
Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework
Cheol-Hui Lee
Hakseung Kim
Byung C. Yoon
Dong-Joo Kim
38
0
0
18 Feb 2025
SWIM: Short-Window CNN Integrated with Mamba for EEG-Based Auditory
  Spatial Attention Decoding
SWIM: Short-Window CNN Integrated with Mamba for EEG-Based Auditory Spatial Attention Decoding
Ziyang Zhang
Andrew Thwaites
Alexandra Woolgar
Brian Moore
Chao Zhang
Mamba
47
1
0
30 Sep 2024
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
258
7,337
0
11 Nov 2021
BENDR: using transformers and a contrastive self-supervised learning
  task to learn from massive amounts of EEG data
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data
Demetres Kostas
Stephane Aroca-Ouellette
Frank Rudzicz
SSL
41
198
0
28 Jan 2021
1