Hybrid Convolutional Neural Network - Long Short-Term Memory Model for Automated Detection of Sleep Stages-Reference-Cited by-同舟云学术

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Hybrid Convolutional Neural Network - Long Short-Term Memory Model for Automated Detection of Sleep Stages

Published:2023-02-09 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS)
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Author:

Sudhamathy G.¹,Valliammal N.¹,Subashini P.¹,Dhivyanrabha T.T.²,Sneha R. Gracelin¹

Affiliation:

1. Avinashilingam Institute for Home Science and Higher Education for Women,Department of Computer Science,Coimbatore,India

2. Centre for Machine Learning and Intelligence Avinashilingam Institute for Home Science and Higher Education for Women,Coimbatore,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099476/10100336/10100489.pdf?arnumber=10100489

Reference20 articles.

1. Subject-adaptive real-time sleep stage classification based on the conditional random eld;luo;AMIA Annual Symposium Proceedings,0

2. DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG

3. ANALYSIS AND AUTOMATIC IDENTIFICATION OF SLEEP STAGES USING HIGHER ORDER SPECTRA

4. Automatic Sleep Staging using Support Vector Machines with Posterior Probability Estimates

5. Sleep EDF Database;kemp;PhysioNet,2013

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