Abstract:Deep learning methods are widely used in the domain of change detection in remote sensing images. While datasets of that kind are abundant, annotated images, specific for the task at hand, are still scarce. Neural networks trained with Self supervised learning aim to harness large volumes of unlabeled satellite high resolution images to help in finding better solutions for the change detection problem. In this paper we experiment with this approach by presenting 4 different change detection methodologies. We p… Show more
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