AlphaUncommon
Azure/pixel_level_land_classification
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
Archived: this repository is read-only
- Owner
- Azure (organization)
- Stars
- Stars: 281
- Forks
- Forks: 96
- Language
- Jupyter Notebook
- License
- MIT
- Created
- 2018
- Topics
- neural-networksimage-classificationimage-segmentationgeospatial-datageospatial-analysisland-coverland-usecntkcntk-modelazure-batchai
- Tier
- Alpha (250 to 699 ★) What this tier means
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