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The paper present a novel method for medical image classification using fuzzy support vector machines (FSVM). In this method a membership degree is defined for each training sample, which can resolve the problem of unclassifiable regions in SVM. Experiments on images of mammography with different noise levels were conducted and results show that the proposed method is able to classify the breast cancer...
The supplier's cooperative design enables the enterprise to use supplier's technical ability fully, reduce the time of product coming into the market, improve quality, and reduce cost. Aiming at the problem of how to evaluate the supplier cooperative design ability (SCDA), this paper constructs the evaluating indices system that is composed of product concept and functional design support ability,...
In this paper we report our experience using different types of wavelets and different SVM kernel functions for classification of Magnetic Resonance Images to identify those showing symptoms of Alzheimer's Disease. We have developed a novel computational framework for extracting discriminative Gabor wavelet features from the images for classification using Support Vector Machines with various kernel...
A novel method for classification of magnetic resonance brain images is presented in this paper. We construct a computational framework for discriminative image feature subspaces. Magnetic resonance images of patients in Alzheimer's disease and normal brain MR images are classified with support vector machines. The framework for the novel method bases on the extraction of gabor features from 2D-magnetic...
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