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We propose a non-homogeneous conditional random field (CRF) built over an adjacency graph of superpixels for contextual region grouping. Our model includes spatially dependent potentials that capture contextual interactions of the data as well as the labels. Both superpixels and segments are described with local statistics which take into account their contexts in the image. This results the non-homogeneity...
In this paper, we present a probabilistic framework for edge and region grouping using conditional random field. Our model is built on a hybrid adjacency graph of atomic region and contour primitives. Unary and pairwise potentials that capture similarity, proximity and curvilinear continuity are defined. Similarity, for both region and edge cues, is measured by likelihood ratios learned from a human...
Even women in technical professional programs in a Taiwan university in 2003 continue to be less receptive than men to uses of instructional computing. The pace of adoption of cyberlearning is influenced by gender factors. Although Taiwan is a semi-conductor world leader, university women in technical universities have not been as receptive as men toward Web-based distance learning. This study used...
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