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 56 (0 this week)
Watchers 3 (0 this week)
Forks 16
License unknown
Ranking

RepositoryStats indexes 638,560 repositories, of these UNITAR-UNOSAT/UNOSAT-AI-Based-Rapid-Mapping-Service is ranked #458,519 (28th percentile) for total stargazers, and #420,389 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #12,118/19,319.

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Recent Commit History

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

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Issue History

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Languages

The primary language is Jupyter Notebook but there's also others...

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updated: 2025-03-26 @ 07:59am, id: 259596581 / R_kgDOD3khJQ