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In this study, a multi-level medical image semantic modeling approach based on fuzzy Bayesian networks is proposed. Its two forms are built. The one is a Bayesian network embedding Conditional Gaussian (CG) models, called BN-CG, and another is a Bayesian network embedding Gaussian mixture model (GMM), called BN-GMM. CG and GMM are employed to implement a fuzzy procedure to perform the soft quantification...
Typical unsupervised feature selection algorithms select a common feature subset for all the clusters. Consequently, clusters embedded in different feature subspaces are not discovered. In this paper, we propose a novel approach of simultaneous localized feature selection and model detection for unsupervised learning. In our approach, local feature saliency, together with other parameters of Gaussian...
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