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It is an important method to help doctor's clinical diagnosis that using pattern recognition technology recognizes and counts Urine Sediment's visible component. Harr wavelet feature has good property of distinguish different components, the proposed method using AdaBoost to select a little part typical Harr feature which are taken as input data of SVM. The trained several bi-class SVM classifiers...
Relevance vector machines have been successfully used in many domains, while their application in software reliability prediction is still quite rare. We proposed an RVM-based model for software reliability prediction, the RVM learning scheme is applied to the failure time data, forcing the network to learn and recognize the inherent internal temporal property of software failure sequence in order...
In this paper, an iterative algorithm, which is based on support vector machine (SVM), is proposed for synthetic aperture radar (SAR) image segmentation. The proposed method considers the SAR image segmentation as the pixel classification. The pixels of the previous segmented image are regarded as the training samples for SVM, which is used to re-segment the image. These iterations are repeated until...
Support vector machines (SVM) has been widely applied in the area of content-based image retrieval in order to learn high-level concepts from low-level image features. Most existing SVM based image retrieval algorithms only rely on global-based features to represent the image content, which obviously can not well reflect the image semantic content. Region-based representations are far more close to...
The samples are assumed to distribute normally in the solution of the standard proximal support vector machine (PSVM). But in many application problems, the data set for each class is generally unbalanced, where a poor performance can be gotten by PSVM. For this, a novel PSVM is presented, namely the modified PSVM (MPSVM). By adding a new diagonal matrix in the primal optimization problem, the new...
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