UNITAR-UNOSAT / UNOSAT-AI-Based-Rapid-Mapping-Service

This GitHub repository contains the machine learning models described in Edoardo Nemnni, Joseph Bullock, Samir Belabbes, Lars Bromley Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery.

UNITAR-UNOSAT
UNITAR-UNOSAT
Date Created 2020-04-28 (4 years ago)
Commits 76 (last one about a year ago)
Stargazers 52 (0 this week)
Watchers 4 (0 this week)
Forks 15
License unknown
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RepositoryStats indexes 583,081 repositories, of these UNITAR-UNOSAT/UNOSAT-AI-Based-Rapid-Mapping-Service is ranked #449,870 (23rd percentile) for total stargazers, and #372,895 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #11,689/17,045.

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4 commits on the default branch (master) since jan '22

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updated: 2024-11-05 @ 02:18am, id: 259596581 / R_kgDOD3khJQ