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DL4MicEverywhere: deep learning for microscopy made flexible, shareable and reproducible
A framework that makes deep-learning pipelines for microscopy flexible, shareable, and reproducible across computing environments.
Ivan Hidalgo-Cenalmor
,
Joanna W. Pylvanainen
,
Mariana G. Ferreira
,
Craig T. Russell
,
Alon Saguy
,
Ignacio Arganda-Carreras
,
Yoav Shechtman
,
Arrate Munoz-Barrutia
,
Beatriz Serrano-Solano
,
Caterina Fuster-Barceló
,
Constantin Pape
,
Emma Lundberg
,
Florian Jug
,
Joran Deschamps
,
Matthew Hartley
,
Mehdi Seifi
,
Teresa Zulueta-Coarasa
,
Vera Galinova
,
Wei Ouyang
,
Guillaume Jacquemet
,
Ricardo Henriques
,
Estibaliz Gomez de Mariscal
DOI
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