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Titlebook: Image Analysis and Recognition; 9th International Co Aurélio Campilho,Mohamed Kamel Conference proceedings 2012 Springer-Verlag Berlin Heid

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-Nearest Neighbor Classification Using Dissimilarity Incrementsl characterization of the datasets. That characterization consists of a high order dissimilarity called dissimilarity increment; this dissimilarity measure uses information from three points at a time, unlike typical distances which are pairwise measures. In practice, in this model, the likelihood o
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Using Permutation Tests to Study How the Dimensionality, the Number of Classes, and the Number of Sa statistic to measure the difference between two or more populations. Then, to estimate the .-value(s), the test error is compared to a set of permuted test-error(s), which is usually obtained after permuting the labels of the populations. In this study, we investigate how several dataset factors, e
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Determining the Number of Clusters with Rate-Distortion Curve Modelingal number of clusters in a data set which is based on a parametric model of a Rate-Distortion curve. Theproposed method can be used in conjunction with any suitable clustering algorithm. It was tested with artificial and real numerical data sets and the results of experiments demonstrate empirically
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Hierarchical Classification-Based Region Growing (HCBRG): A Collaborative Approach for Object Segmenclassification steps is one of the major limits of these approaches. In this paper, we introduce a hierarchical classification based on a region growing approach driven by expert knowledge represented in a concept hierarchy. In order to overcome the region growing’s limits, a first classification wi
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Max and Min Values of the Structural Similarity Function ,(,,,) on the ,, Sphere ,,(,), , ∈ ℝ,icting ourselves to points . that lie on an .. sphere centered at . with fixed radius .. To do this, we employ the method of Lagrange multipliers and show that at least four (and as many as six) critical points exist, deriving the conditions that guarantee their existence.
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