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On the generation of realistic synthetic petrographic datasets using a style-based GAN
Deep learning architectures have transformed data analytics in geosciences, complementing traditional approaches to geological problems. Although deep learning applications in geosciences show encouraging signs, their potential remains untapped due to limited data availability and the required in-de...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9334578/ https://www.ncbi.nlm.nih.gov/pubmed/35902601 http://dx.doi.org/10.1038/s41598-022-16034-4 |