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AUTOMATIC REFINEMENT OF TRAINING DATA FOR CLASSIFICATION OF SATELLITE IMAGERY
2012
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
In this paper, we present a method for automatic refinement of training data. Many classifiers from machine learning used in applications in the remote sensing domain, rely on previously labelled training data. This labelling is often done by human operators and is bound to time constraints. Hence, selection of training data must be kept practical which implies a certain inaccuracy. This results in erroneously tagged regions enclosed within competing classes. For that purpose, we propose a
doi:10.5194/isprsannals-i-7-117-2012
fatcat:7u6eblvoijetje4v7d4iych5rm