ImJoy: an open-source computational platform for the deep learning era

Wei Ouyang, Florian Mueller, Martin Hjelmare, Emma Lundberg, Christophe Zimmer
5/30/2019
cs.LGq-bio.QMstat.ML

Official code: imjoy-team/ImJoy (190 stars, MIT, last commit 2023-10-12). 1 more implementation below.

Abstract

Deep learning methods have shown extraordinary potential for analyzing very diverse biomedical data, but their dissemination beyond developers is hindered by important computational hurdles. We introduce ImJoy (https://imjoy.io/), a flexible and open-source browser-based platform designed to facilitate widespread reuse of deep learning solutions in biomedical research. We highlight ImJoy's main features and illustrate its functionalities with deep learning plugins for mobile and interactive image analysis and genomics.

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Code Implementations(2)

imjoy-team/ImJoyOfficial100%
MIT

ImJoy: Deep Learning Made Easy!

19034CSS, VueJun 18, 20183 years agoMIT
deep-learningimage-processingimjoyjavascriptpython+1 more
imjoy-team/example-pluginsOfficial100%
MIT
151HTML, JavaScriptApr 9, 20195 years agoMIT

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Cite this paper

@article{ouyang2019imjoy,
  title  = {ImJoy: an open-source computational platform for the deep learning era},
  author = {Wei Ouyang and Florian Mueller and Martin Hjelmare and Emma Lundberg and Christophe Zimmer},
  year   = {2019},
  eprint = {1905.13105},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1905.13105}
}

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