Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most eff...

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Bibliographic Details
Main Authors:	Paolo Napoletano, Flavio Piccoli, Raimondo Schettini
Format:	Article
Language:	English
Published:	MDPI AG 2018-01-01
Series:	Sensors
Subjects:	anomaly detection defect detection industrial quality inspection quality control convolutional neural networks, nanofibrous materials
Online Access:	http://www.mdpi.com/1424-8220/18/1/209

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