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Connectivity-informed drainage network generation using deep convolution generative adversarial networks
Stochastic network modeling is often limited by high computational costs to generate a large number of networks enough for meaningful statistical evaluation. In this study, Deep Convolutional Generative Adversarial Networks (DCGANs) were applied to quickly reproduce drainage networks from the alread...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7810735/ https://www.ncbi.nlm.nih.gov/pubmed/33452322 http://dx.doi.org/10.1038/s41598-020-80300-6 |