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Automated Approach To Classification Of Mine-Like Objects Using Multiple-Aspect Sonar Images
2014
Journal of Artificial Intelligence and Soft Computing Research
In this paper, the detection of mines or other objects on the seabed from multiple side-scan sonar views is considered. Two frameworks are provided for this kind of classification. The first framework is based upon the Dempster–Shafer (DS) concept of fusion from a single-view kernel-based classifier and the second framework is based upon the concepts of multi-instance classifiers. Moreover, we consider the class imbalance problem which is always presents in sonar image recognition. Our
doi:10.1515/jaiscr-2015-0004
fatcat:lglqmlgpmnhxleu3hsaunoysgq