Super-resolving 3D nanostructures using artificially generated image data and spatial transport simulations
An approach for deploying stochastic three-dimensional (3D) models to generate microstructural 3D image data for training super-resolution networks is investigated for three different scaling factors $\alpha\in\{2,4,8\}$ . The presented approach addresses the issue of scarcity in training data by tr...
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| Autori principali: | , , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
IOP Publishing
2025-01-01
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| Serie: | Machine Learning: Science and Technology |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1088/2632-2153/ae0c55 |
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