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Small infrared target detection is one of the key techniques in infrared searching and tracking applications. A novel small target detection method based on the complex filter bank is proposed in this paper. Firstly, a training sample dataset is built and the complex filter bank is utilized to extract the feature representation of each pixel. Then, the support vector machine is used to detect the...
While systematic reviews (SRs) are positioned as an essential element of modern evidence-based medical practice, the creation and update of these reviews is resource intensive. In this research, we propose to leverage advanced analytics techniques for automatically classifying articles for inclusion and exclusion for systematic review update. Specifically, we used the soft-margin Support Vector Machine...
In this paper, we investigate the classification of masses with texture features. We propose an improved level set method to find the boundary of a mass, based on the initial contour provided by radiologists. After the boundary of a mass is found, texture features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the surrounding area of the boundary of the mass. The extracted texture...
Three dimension finite element model (3D-FEM) of the spherical motor is presented in this paper. By analysis of one pair of stator-rotor poles, nonlinear regression model of one pair of stator-rotor poles based on the support vector machine (SVM) is introduced. Parameters optimization of one pair of stator-rotor poles for the maximal torque is also introduced which is based on chaos and uses the SVM...
By applying the method of support vector machine, we carry on a classification study of existing diagram data of the Chinese herbal medicine fingerprint. We compared the effect of support vector machine algorithm on two and several types of data identification with that of the existing computer classification methods. It is shown that the support vector machine method can be used to identify Chinese...
The principle and the method for correcting the nonlinear errors of the sensor system with least square SVM (LS-SVM) are introduced. The basic principle of LS-SVM is presented. In order to get the optimal parameters of LS-SVM automatically, use adaptive genetic algorithm (AGA) to select parameters of LS-SVM, and use AGA-least square SVM to nonlinear calibration of temperature sensor. Experimental...
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