On the generation of realistic synthetic petrographic datasets using a style-based GAN
Abstract 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 requi...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
Nature Portfolio
2022-07-01
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| Series: | Scientific Reports |
| Acceso en liña: | https://doi.org/10.1038/s41598-022-16034-4 |
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