Object detection and image segmentation have always been a big task in the field of geospatial sciences. With the growth of open satellite and aerial images, focus on this field is getting bigger and bigger.
In the general computer vision field, there is one big term shaking the field in the last years - artificial neural networks. Artificial neural networks and especially their subtype called convolutional neural networks brought into the field of computer vision precisions which were just a few years ago still considered as not imaginable.
We had decided to connect those two fields and test the use of artificial neural networks on satellite and aerial images. A suite of modules using convolutional neural networks was implemented into GRASS GIS.
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