PROCESS
Providing computing solutions for exascale challenges
CamNet containers
Recipes to create Docker containers for each of the CamNet layers
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What CamNet containers can do for you
- docker container definitions for CamNET Layer 1, 2, and 3
- easy to set up and deploy to new compute infrastructures
This repository contains recipes to create docker containers for each of the three CamNet layers. CamNET is a deep learning platform for digital histopathology aimed at detecting tumor tissue in gigapixel scans of slides containing breast lymph nodes tissue. These docker containers enable easy deployment of CamNet on various infrastructures.
Tags
Programming Language
- Shell scripts
License
- MIT
Source code
Participating organizations
Mentions
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Visualizing and Interpreting Feature Reuse of Pretrained CNNs for HistopathologyAugust 08, 2019
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Machine Learning in Medical ImagingJanuary 10, 2019
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Interpreting Intentionally Flawed Models with Linear ProbesOctober 22, 2019
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Improved interpretability for computer-aided severity assessment of retinopathy of prematurityMarch 13, 2019
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D2.1 Progress Report (Use Cases #1-5)October 31, 2018
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D2.2 Progress report (UC#1-5) - updateOctober 31, 2019
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D3.2 Performance modelling and prediction - progress reportOctober 31, 2019
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D4.1 Initial state of the art and requirements analysis, initial PROCESS architectureApril 30, 2018
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D4.3 Updated Requirements Analysis, Validation of 1st Prototype and Updated PROCESS ArchitectureApril 30, 2019
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D4.5 Validation of 2nd prototype and final PROCESS architectureJanuary 31, 2020
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D8.1 Validation Report of 1st PROCESS UpdateJuly 31, 2019
Projects with CamNet containers
Contributors
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Mara GrazianiHaute École Spécialisée de Suisse Occidentale HES-SO Valais (HESSO)
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Ivan EggelHaute École Spécialisée de Suisse Occidentale HES-SO Valais (HESSO)
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