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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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| Publicado no: | Sensors (Basel) |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5795842/ https://ncbi.nlm.nih.gov/pubmed/29329268 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s18010209 |
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