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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Vydané v:	Engineering applications of artificial intelligence Ročník 120; s. 105838
Hlavní autori:	Langarica, Saúl, Núñez, Felipe
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.04.2023
Predmet:	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
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