GitHub / 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.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Azure%2Fpixel_level_land_classification

Topics: azure-batchai, azure-storage, cntk, cntk-model, geospatial-analysis, geospatial-data, image-classification, image-segmentation, land-cover, land-use, microsoft, microsoft-azure, microsoft-machine-learning, neural-networks

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