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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...
Autores principales: | 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 |
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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/PMC8050272/ https://www.ncbi.nlm.nih.gov/pubmed/33859193 http://dx.doi.org/10.1038/s41467-021-22518-0 |
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