Democratising deep learning for microscopy with ZeroCostDL4Mic

Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources to train DL networks leads to an accessibility bar...

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Detalhes bibliográficos
Publicado no:Nat Commun
Main Authors: von Chamier, Lucas, Laine, Romain F., Jukkala, Johanna, Spahn, Christoph, Krentzel, Daniel, Nehme, Elias, Lerche, Martina, Hernández-Pérez, Sara, Mattila, Pieta K., Karinou, Eleni, Holden, Séamus, Solak, Ahmet Can, Krull, Alexander, Buchholz, Tim-Oliver, Jones, Martin L., Royer, Loïc A., Leterrier, Christophe, Shechtman, Yoav, Jug, Florian, Heilemann, Mike, Jacquemet, Guillaume, Henriques, Ricardo
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2021
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8050272/
https://ncbi.nlm.nih.gov/pubmed/33859193
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-021-22518-0
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