Anomaly Detection in Sleep Habits Using Deep Learning-Reference-Cited by-同舟云学术

Anomaly Detection in Sleep Habits Using Deep Learning

Published:2023-08-26 Issue: Volume: Page:
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Container-title:2023 IEEE 19th International Conference on Automation Science and Engineering (CASE)
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Author:

Gasmi Asma¹,Augusto Vincent¹,Faucheu Jenny²,Morin Claire³,Serpaggi Xavier⁴

Affiliation:

1. Mines Saint-Etienne, Univ Clermont Auvergne, CNRS, UMR 6158 LIMOS, Center for Biomedical and Healthcare Engineering,Saint-Etienne,France,F-42023

2. Centre SMS,Mines Saint-Etienne, CNRS, UMR 5307 Laboratoire Georges Friedel,Saint-Etienne,France,F-42023

3. Mines Saint-Etienne, Univ Lyon, Univ Jean Monnet, INSERM, UMR 1059 Sainbiose, Centre CIS,Saint-Etienne,France,F-42023

4. Mines Saint-Étienne, Institut Henri Fayol,Département ISI,Saint-Étienne,France,F-42023

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10260321/10260291/10260617.pdf?arnumber=10260617

Reference23 articles.

1. Using deep networks for fraud detection in the credit card transactions

2. Credit Card Fraud Detection using autoencoder based clustering

3. Sleep Anomalies and Mood Disorders: A Review Study of Adults;shukla;The International Journal of Indian Psychology,2022

4. Relationship between Sleep Disorders and Health Related Quality of Life—Results from the Georgia SOMNUS Study

5. Anomaly De-tection in Credit Card Transaction using Deep Learning Techniques;ketepalli;2022 7th International Conference on Communication and Electronics Systems (ICCES),0

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