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