ZeroCostDL4Mic: exploiting Google Colab to develop a free and open-source toolbox for Deep-Learning in microscopy
Tl;dr: this wiki page has everything you need to get started.
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.
| Running a ZeroCostDL4Mic notebook | Example data in ZeroCostDL4Mic |
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Any researcher interested in microscopy, independent of their background training. ZeroCostDL4Mic is designed for anyone with little or no coding expertise to quickly test, train and use popular Deep-Learning networks used to process microscopy data.
While this project is developed as a collaboration lead by the Jacquemet and Henriques laboratories, there is a long list of contributors associated with the project acknowledged in our preprint and in the wiki page.
Lucas von Chamier, Johanna Jukkala, Christoph Spahn, Martina Lerche, Sara Hernández-pérez, Pieta Mattila, Eleni Karinou, Seamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Florian Jug, Loïc Alain Royer, Mike Heilemann, Romain F. Laine, Guillaume Jacquemet, Ricardo Henriques. ZeroCostDL4Mic: an open platform to simplify access and use of Deep-Learning in Microscopy. bioRxiv, 2020. DOI: https://doi.org/10.1101/2020.03.20.000133
