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.
microsoft
cntk
geospatial-data
neural-networks
image-classification
image-segmentation
azure-storage
land-cover
land-use
geospatial-analysis
microsoft-azure
microsoft-machine-learning
cntk-model
azure-batchai
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Updated
Jul 25, 2019 - Jupyter Notebook