OutlierNets: Highly Compact Deep Autoencoder Network Architectures for On-Device Acoustic Anomaly Detection

Human operators often diagnose industrial machinery via anomalous sounds. Given the new advances in the field of machine learning, automated acoustic anomaly detection can lead to reliable maintenance of machinery. However, deep learning-driven anomaly detection methods often require an extensive am...

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Bibliographic Details

Published in:	Sensors (Basel, Switzerland) Vol. 21; no. 14; p. 4805
Main Authors:	Abbasi, Saad, Famouri, Mahmoud, Shafiee, Mohammad Javad, Wong, Alexander
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 14.07.2021 MDPI
Subjects:	Accuracy acoustic anomaly detection Acoustics Communication Datasets Deep learning Design embedded machine learning Machine learning Neural networks Receivers & amplifiers Sound Support vector machines unsupervised learning
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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