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

Internet

http://www.mdpi.com/1424-8220/18/1/209

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