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#### Initiative Overview
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* [Overview - Description of available models, codes and datasets](https://gitlab.version.fz-juelich.de/MLDL_FZJ/juhaicu/jsc_public/sharedspace/playground/covid_xray_deeplearning/wiki/-/blob/master/Description.md)
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* Spin-off project in frame of Helmholtz Information & Data Science Academy ([HIDA](https://www.helmholtz-hida.de/)) [Israel Exchange Program](https://idsi.net.technion.ac.il/call-for-student-helmholtz-israel-virtual-exchange-program/) (application deadline: 07.05.2021)
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- [Large Scale Transfer Learning applied to X-Ray based COVID-19 diagnostics](https://idsi.net.technion.ac.il/12-large-scale-supervised-and-unsupervised-deep-learning-for-fast-and-robust-transfer-on-medical-x-ray-imaging-datasets-applied-to-covid-19-diagnostics/)
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* For model training and further experiments, **computing budget is available**,
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- **UPDATE**: 30.10.2020 - COVIDNetX computational time application granted for JUWELS Booster (ca. **3600 GPUs** !)
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- Grant title: *"Large-Scale Advanced Deep Transfer Learning for Fast, Robust and Affordable COVID-19 X-Ray Diagnostics"*
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