GI-SleepNet: A Highly Versatile Image-Based Sleep Classification Using a Deep Learning Algorithm

GI-SleepNet: A Highly Versatile Image-Based Sleep Classification Using a Deep Learning Algorithm

Sleep-stage classification is essential for sleep research. Various automatic judgment programs, including deep learning algorithms using artificial intelligence (AI), have been developed, but have limitations with regard to data format compatibility, human interpretability, cost, and technical requ...

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Bibliographic Details
Main Authors: Tianxiang Gao, Jiayi Li, Yuji Watanabe, Chijung Hung, Akihiro Yamanaka, Kazumasa Horie, Masashi Yanagisawa, Masahiro Ohsawa, Kazuhiko Kume
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Clocks & Sleep
Subjects:
EEG
sleep scoring
2D-CNN
GANs
tiny dataset
Online Access:https://www.mdpi.com/2624-5175/3/4/41

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