# NRCan/geo-deep-learning

<https://repo.masters-masters.com/en/repos/NRCan/geo-deep-learning>

[Home](https://repo.masters-masters.com/en) › [NRCan](https://repo.masters-masters.com/en/owners/NRCan) › [geo-deep-learning](https://repo.masters-masters.com/en/repos/NRCan/geo-deep-learning)

NRCan/geo-deep-learning has 206 stars on GitHub. Its RepoMasters card: Prototype tier. Deep learning applied to georeferenced datasets

| Field | Value |
| --- | --- |
| Owner | [NRCan](https://repo.masters-masters.com/en/owners/NRCan) |
| Stars | 206 |
| Forks | 72 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | MIT |
| Created | 2018 |
| Topics | deep-learning, cnn, pytorch, unet, semantic-segmentation, deeplabv3, remote-sensing |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [NRCan/geo-deep-learning](https://github.com/NRCan/geo-deep-learning) |

## Repository

Deep learning applied to georeferenced datasets

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.