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The support vector machine(SVM) based on structural risk minimization is more and more widely used to solve the problems of small sample, nonlinear, high dimensional and local minimization attributes because of its good generalization. But the performance of SVM is influenced by the model parameters very much. At present there is not a unified method of model selection, which makes it troublesome...
Image class segmentation is a problem that combines image segmentation and image classification. Conditional random field can be used in image class segmentation to achieve state-of-the-art result, adding high-level information in the course of using low-level cues to conduct segmentation. In this paper we introduce a method using weighted neighborhood histogram on the over-segmented original images...
Reducing dimension processing is needed in feature samples because the repeated and secondary features would reduce the classification ability and increase computation complexity. In this paper, a feature selection method, named MPSO (Modified Particle Swarm Optimization), is proposed. The original group velocity of a particle swarm was changed into two separate and parallel particle swarm velocity,...
A relatively unexplored problem in facial expression analysis is how to select the positive and negative samples with which to train classifiers for expression recognition. Typically, for each action unit (AU) or other expression, the peak frames are selected as positive class and the negative samples are selected from other AUs. This approach suffers from at least two drawbacks. One, because many...
In this paper a novel linear regression model is proposed to mine related queries from query logs. Three types of association relationships between queries are identified and leveraged in our model, which include query session co-occurence, URL-clicked sharing and text similarity. Previous work directly applies part of these relations, which may be largely affected by the noise in query logs, such...
The purpose of this study was to explore the automatic method of detecting the gray matter loss of Alzheimerpsilas disease (AD) patients with magnetic resonance imaging (MRI). In this paper, voxel-based morphometry (VBM) and support vector machine (SVM )were combined and introduced to diagnose Alzheimer's disease(AD) for clinical applications. Firstly, with the VBM method, 20 features were obtained...
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