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08/2020 - BioRxiv

ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy

Autori:

  • Von Chamier L.,
  • Laine R. F.,
  • Jukkala J.,
  • Spahn C.,
  • Krentzel D.,
  • Nehme E.,
  • Lerche M.,
  • Hernández-Pérez S.,
  • Mattila P. K.,
  • Karinou E.,
  • Holden S.,
  • Solak A. C.,
  • Krull A.,
  • Buchholz T.,
  • Jones M. L.,
  • Royer L. A.,
  • Leterrier C.,
  • Shechtman Y.,
  • Jug F.,
  • Heilemann M.,
  • Jacquemet G.,
  • Henriques R.

Sommario:

The resources and expertise needed to use Deep Learning (DL) in bioimaging remain significant barriers for most laboratories. We present https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki, a platform simplifying access to DL by exploiting the free, cloud-based computational resources of Google Colab. https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki allows researchers to train, evaluate, and apply key DL networks to perform tasks including segmentation, detection, denoising, restoration, resolution enhancement and image-to-image translation. We demonstrate the application of the platform to study multiple biological processes.

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