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Vector-Map-Generation-from-Aerial-Imagery-using-Deep-Learning-GeoSpatial-UNET

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We propose a simple yet efficient technique to leverage semantic segmentation model to extract and separate individual buildings in densely compacted areas using medium resolution satellite/UAV orthoimages. We adopted standard UNET architecture, additionally added batch normalization layer after every convolution, to label every pixel in the image.

Creat2019-04-12T02:57:43
Update2025-01-15T17:00:12
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