Decision Support with Belief Functions Theory for Seabed Characterization
Arnaud Martin,
Isabelle Quidu
Abstract:The seabed characterization from sonar images is a very hard task because of the produced data and the unknown environment, even for an human expert. In this work we propose an original approach in order to combine binary classifiers arising from different kinds of strategies such as one-versusone or one-versus-rest, usually used in the SVM-classification. The decision functions coming from these binary classifiers are interpreted in terms of belief functions in order to combine these functions with one of the… Show more
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