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DeepImageJ: A user-friendly environment to run deep learning models in ImageJ
View ORCID ProfileEstibaliz Gómez-de-Mariscal, Carlos García-López-de-Haro, View ORCID ProfileWei Ouyang, Laurène Donati, View ORCID ProfileEmma Lundberg, Michael Unser, View ORCID ProfileArrate Muñoz-Barrutia, Daniel Sage
doi: https://doi.org/10.1101/799270
Estibaliz Gómez-de-Mariscal
1Bioengineering and Aerospace, Engineering Department, Universidad Carlos III de Madrid and Instituto de Investigación Sanitaria, Gregorio Marañón, Madrid, Spain
Carlos García-López-de-Haro
1Bioengineering and Aerospace, Engineering Department, Universidad Carlos III de Madrid and Instituto de Investigación Sanitaria, Gregorio Marañón, Madrid, Spain
Wei Ouyang
3Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
Laurène Donati
4EPFL Center for Imaging, École polytechnique fédérale, de Lausanne (EPFL), Lausanne, Switzerland
Emma Lundberg
3Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
Michael Unser
6Biomedical Imaging Group, École polytechnique fédérale, de Lausanne (EPFL), Lausanne, Switzerland
Arrate Muñoz-Barrutia
1Bioengineering and Aerospace, Engineering Department, Universidad Carlos III de Madrid and Instituto de Investigación Sanitaria, Gregorio Marañón, Madrid, Spain
Daniel Sage
6Biomedical Imaging Group, École polytechnique fédérale, de Lausanne (EPFL), Lausanne, Switzerland
Article usage
Posted May 06, 2021.
DeepImageJ: A user-friendly environment to run deep learning models in ImageJ
Estibaliz Gómez-de-Mariscal, Carlos García-López-de-Haro, Wei Ouyang, Laurène Donati, Emma Lundberg, Michael Unser, Arrate Muñoz-Barrutia, Daniel Sage
bioRxiv 799270; doi: https://doi.org/10.1101/799270
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