it COMBINING PARAMETRIC AND NON-PARAMETRIC ALGORITHMS FOR A PARTIALLY UNSUPERVISED CLASSIFICATION OF MULTITEMPORAL REMOTE-SENSING IMAGES

Abstract

In this paper, we propose a classification system based on a multiple-classifier architecture, which is aimed at updating land-cover maps by using multisensor and/or multisource remote-sensing images. The proposed system is composed of an ensemble of classifiers that, once trained in a supervised way on a specific image of a given area, can be retrained in… (More)

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