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 51 (0 this week)
Watchers 4 (0 this week)
Forks 14
License unknown
Ranking

RepositoryStats indexes 565,279 repositories, of these UNITAR-UNOSAT/UNOSAT-AI-Based-Rapid-Mapping-Service is ranked #444,924 (21st percentile) for total stargazers, and #366,496 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #11,481/16,285.

Star History

Github stargazers over time

Watcher History

Github watchers over time, collection started in '23

Recent Commit History

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

Yearly Commits

Commits to the default branch (master) per year

Issue History

Languages

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

updated: 2024-09-04 @ 04:47pm, id: 259596581 / R_kgDOD3khJQ