Learning CRF potentials through fully convolutional networks for satellite image semantic segmentation
Martina Pastorino,
Gabriele Moser,
Sebastiano B. Serpico
et al.
Abstract:This paper introduces a method to automatically learn the unary and pairwise potentials of a conditional random field (CRF) from the input data in a non-parametric fashion, within the framework of the semantic segmentation of remote sensing images. The proposed model is based on fully convolutional networks (FCNs) and fully connected neural networks (FCNNs) to extensively exploit the semantic and spatial information contained in the input data and in the intermediate layers of an FCN. The idea of the model is … Show more
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