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Approaches to Training Multi-Class Semantic Image Segmentation of Damage in Concrete
This paper addresses the problem of creating a large quantity of high-quality training segmentation masks from scanning electron microscopy (SEM) images. The images are acquired from concrete samples that exhibit progressive amounts of degradation resulting from alkali-silica reaction (ASR), a leadi...
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| Pubblicato in: | J Microsc |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7849179/ https://ncbi.nlm.nih.gov/pubmed/32406521 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/jmi.12906 |
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