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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Detalles Bibliográficos
Autores principales: Abbasi, Saad, Famouri, Mahmoud, Shafiee, Mohammad Javad, Wong, Alexander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8309714/
https://www.ncbi.nlm.nih.gov/pubmed/34300545
http://dx.doi.org/10.3390/s21144805

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8309714/
https://www.ncbi.nlm.nih.gov/pubmed/34300545
http://dx.doi.org/10.3390/s21144805

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