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Generative modeling for renal microanatomy
Generative adversarial networks (GANs) have received immense attention in the field of machine learning for their potential to learn high-dimensional and real data distribution. These methods do not rely on any assumptions about the data distribution of the input sample and can generate real-like sa...
Uloženo v:
| Vydáno v: | Proc SPIE Int Soc Opt Eng |
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| Hlavní autoři: | , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7194215/ https://ncbi.nlm.nih.gov/pubmed/32362707 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1117/12.2549891 |
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