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Generating Input Data for Microstructure Modelling: A Deep Learning Approach Using Generative Adversarial Networks
For the generation of representative volume elements a statistical description of the relevant parameters is necessary. These parameters usually describe the geometric structure of a single grain. Commonly, parameters like area, aspect ratio, and slope of the grain axis relative to the rolling direc...
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| Publicado no: | Materials (Basel) |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7579462/ https://ncbi.nlm.nih.gov/pubmed/32977556 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ma13194236 |
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