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This paper presents a condensed semantic tree model for representing image category. For a specific application area, a semantic concept space is defined. According to the annotation for an image, a real-value semantic vector is gained that describes the content of it. In order to represent image category, condensed semantic tree model is introduced. It is a triple level structure. The bottom level...
An improved binary tree algorithm is proposed for the practical problem of the relativity position of the data sets for oil-immersed transformer in the pattern feature space. And a fault diagnosis model of dissolved gas analysis (DGA) based on an improved binary tree multi-class support vector machine (SVM) is constructed. This method overcomes the disadvantage that the traditional binary tree, which...
Content-based image retrieval represents images as N-dimensional feature vectors. Similar image retrieval is computed over these high dimensional feature vectors. A sequential scan of the feature vectors for a query method is costly for a large number of images when N is high. The search time and search space can be reduced through indexing the data. In this paper we proposed a hierarchical clustering...
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