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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...

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Bibliografski detalji
Izdano u:Proc SPIE Int Soc Opt Eng
Glavni autori: Murali, Leema Krishna, Lutnick, Brendon, Ginley, Brandon, Tomaszewski, John E., Sarder, Pinaki
Format: Artigo
Jezik:Inglês
Izdano: 2020
Teme:
Online pristup: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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