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InstantDL - An easy-to-use deep learning pipeline for image segmentation and classification

Dominik Waibel, Sayedali Shetab Boushehri, Carsten Marr
doi: https://doi.org/10.1101/2020.06.22.164103

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doi 
https://doi.org/10.1101/2020.06.22.164103
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  • July 2, 2020.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.

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  1. Dominik Waibel1,2,
  2. Sayedali Shetab Boushehri1,3 and
  3. Carsten Marr1,*
  1. 1Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
  2. 2Technical University of Munich, School of Life Sciences, Weihenstephan, Germany
  3. 3Roche Innovation Center Munich, Roche Diagnostics GmbH, Penzberg, Germany
  1. ↵*Corresponding author; email: carsten.marr{at}helmholtz-muenchen.de
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Posted July 02, 2020.
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InstantDL - An easy-to-use deep learning pipeline for image segmentation and classification
Dominik Waibel, Sayedali Shetab Boushehri, Carsten Marr
bioRxiv 2020.06.22.164103; doi: https://doi.org/10.1101/2020.06.22.164103
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