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The image semantic classification is new focus in the image classification field, the traditional classification algorithm is based on the low level visual features, but there is an enormous semantic gap problem between the low-level visual features and high-level semantic information of images. An image semantic classification approach is proposed based on Kernel PCA Support Vector Machines (KPCA...
Orthogonal discriminant analysis algorithms have recently been proposed. However, these methods donpsilat address the singularity problem in the high dimensional feature space. In this paper, we present a new method called direct orthogonal discriminant analysis (DODA), which is able to extract all the orthogonal discriminant vectors simultaneously in the high-dimensional feature space and does not...
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