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In this paper, we consider the problem of classifying a real world image to the corresponding object class based on its visual content via sparse representation, which is originally used as a powerful tool for acquiring, representing and compressing high-dimensional signals. Assuming the intuitive hypothesis that an image could be represented by a linear combination of the training images from the...
In this paper, a new meta-method based on the physical nuclear process is presented. This meta-method called Fusion-Fission is applied to the two different class of graph partitioning problems. This paper presents results found by this method in comparison with results of classical methods for an air traffic management problem, an image segmentation problem and applied to classical benchmarks. All...
Metaheuristics are very useful methods because they can find (approximate) solutions of a great variety of problems. One of them, which interests us, is graph partitioning. We present a new metaheuristic based on nuclear fusion and fission of atoms. This metaheuristic, called fusion fission, is compared to other classical algorithms. First, we present spectral and multilevel algorithms which are used...
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