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Active learning, which has a strong impact on processing data prior to the classification phase, is an active research area within the machine learning community, and is now being extended for remote sensing applications. To be effective, classification must rely on the most informative pixels, while the training set should be as compact as possible. Active learning heuristics provide capability to select unlabeled data that are the "most informative" and to obtain the respective labels,doi:10.1109/jproc.2012.2231951 fatcat:hoyz7vgagfgqfoxjfmwqdjqkvu