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From Cats to Categories: Processing Geospatial Data with Machine and Deep Learning

With the exponential growth of the number of images (and radar data, and point clouds, and…) that are being collected, we must answer this question: how are we going to make sense of all of this data? And even before making sense of it, how are we going to sift through the amount of data to a manageable heap? How do we tell what needs further attention and what can be archived for later? The answer seems to be "Give it to the machines and let them sort it out." Now that might seem a little harsh, but it really makes sense.