M. Maher Ben Ismail

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We propose a new relational clustering approach, called Fuzzy clustering with Learnable Cluster-dependent Kernels (FLeCK), that learns the underlying cluster-dependent dissimilarity measure while seeking compact clusters. The learned dissimilarity is based on a Gaussian kernel function with cluster-dependent parameters. Each cluster’s parameter learned by(More)
Because of their visual characteristic which consists of black background versus white foreground, extracting relevant descriptors from medical X-ray images remains a challenging problem for medical imaging researchers. In this paper, we conduct an empirical comparison of several feature descriptors in order to evaluate their efficiency in content based(More)