Anomaly Detection for Sensor Signals Utilizing Deep Learning Autoencoder-Based Neural Networks

Anomaly detection is a significant task in sensors’ signal processing since interpreting an abnormal signal can lead to making a high-risk decision in terms of sensors’ applications. Deep learning algorithms are effective tools for anomaly detection due to their capability to address imbalanced data...

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Bibliographic Details

Published in:	Bioengineering
Main Authors:	Fatemeh Esmaeili, Erica Cassie, Hong Phan T. Nguyen, Natalie O. V. Plank, Charles P. Unsworth, Alan Wang
Format:	Article
Language:	English
Published:	MDPI AG 2023-03-01
Subjects:	time series anomaly detection outlier detection semi-supervised learning signal processing autoencoder (AE) vanilla autoencoder
Online Access:	https://www.mdpi.com/2306-5354/10/4/405