Contrastive blind denoising autoencoder for real time denoising of industrial IoT sensor data

In an industrial IoT setting, ensuring the quality of sensor data is a must when data-driven algorithms operate on the upper layers of the control system. Unfortunately, the common place in industrial facilities is to find sensor time series heavily corrupted by noise and outliers. This work propose...

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Bibliographic Details

Published in:	Engineering applications of artificial intelligence Vol. 120; p. 105838
Main Authors:	Langarica, Saúl, Núñez, Felipe
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.04.2023
Subjects:	Autoencoders Cyber–physical systems Noise contrastive estimation Self-supervised learning Cyber–physical systems Noise contrastive estimation Autoencoders Self-supervised learning
ISSN:	0952-1976, 1873-6769
Online Access:	Get full text
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