ZeroCostDL4Mic

ZeroCostDL4Mic is a collection of self-explanatory Jupyter Notebooks for Google Colab that features an easy-to-use graphical user interface. They are meant to quickly get you started on learning to use deep-learning for microscopy. Google Colab itself provides the computations resources needed at no-cost. ZeroCostDL4Mic is designed for researchers that have little or no coding expertise to quickly test, train and use popular Deep-Learning networks.

🔗Source-Code Repository

Main publication:

Other publications using resource:

DeepBacs: Bacterial image analysis using open-source deep learning approaches *Christoph Spahn*, *Estibaliz Gómez-de-Mariscal*, *Romain F. Laine*, *Pedro Matos Pereira*, *Estibaliz Gómez-de-Mariscal*, *Lucas von Chamier*, Mia Conduit, Mariana Gomes de Pinho, Guillaume Jacquemet, Séamus Holden, *Mike Heilemann*, Mike Heilemann, *Ricardo Henriques* Published in bioRxiv, November 2021 (see preprint) Research themes: New Methods, Software Type: Preprint, Corresponding author

Avoiding a replication crisis in deep-learning-based bioimage analysis *Romain F Laine*, Ignacio Arganda-Carreras, *Ricardo Henriques*, Guillaume Jacquemet Published in Nature methods, October 2021 (see publication) Research themes: New Methods, Software Type: Paper

Democratising deep learning for microscopy with ZeroCostDL4Mic *Lucas von Chamier*, *Romain F Laine*, Johanna Jukkala, *Christoph Spahn*, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-Pérez, Pieta K Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L Jones, Loïc A Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, *Mike Heilemann*, Mike Heilemann, Guillaume Jacquemet, *Ricardo Henriques* Published in Nature communications, April 2021 (see publication) Research themes: New Methods, Software Type: Paper, Corresponding author