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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Detalles Bibliográficos
Autores principales: Napoletano, Paolo, Piccoli, Flavio, Schettini, Raimondo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795842/
https://www.ncbi.nlm.nih.gov/pubmed/29329268
http://dx.doi.org/10.3390/s18010209

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795842/
https://www.ncbi.nlm.nih.gov/pubmed/29329268
http://dx.doi.org/10.3390/s18010209

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