Pattern recognition with machine learning on optical microscopy images of typical metallurgical microstructures

For advanced materials characterization, a novel and extremely effective approach of pattern recognition in optical microscopic images of steels is demonstrated. It is based on fast Random Forest statistical algorithm of machine learning for reliable and automated segmentation of typical steel micro...

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Detalles Bibliográficos
Autores principales: Bulgarevich, Dmitry S., Tsukamoto, Susumu, Kasuya, Tadashi, Demura, Masahiko, Watanabe, Makoto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794901/
https://www.ncbi.nlm.nih.gov/pubmed/29391483
http://dx.doi.org/10.1038/s41598-018-20438-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5794901/
https://www.ncbi.nlm.nih.gov/pubmed/29391483
http://dx.doi.org/10.1038/s41598-018-20438-6

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