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Recursive projection twin support vector machine (PTSVM) and Locality preserving projection twin support vector machine (LPPTSVM) are two extensions of traditional support vector machine (SVM). However, they may lead to a weak classifier in the application where some data points may not be fully assigned to one class. In this paper, we introduce the basic idea of fuzzy membership into LPPTSVM and...
This paper presents a robust approach to classify the driver state in a novel advanced driver assistance system named ShadeVision, which aims to improve the driving safety and comfort by avoiding the dazzling effect. Different from the existing algorithms for driver state classification, our proposed method is capable of identifying the "dazzled state" of the driver, which can function as...
This paper presents a novel method for detection and recognition of glass defects in low resolution images. First, the defect region is located by the method of Canny edge detection, and thus the smallest connected region (rectangle) can be found. Then, the binary information of the core region can be obtained based on a specific filter. After noises are removed, a novel Binary Feature Histogram (BFH)...
The problem of shadow detection is a challenging assignment in video surveillance systems. There are plentiful research achievements about shadow detection but they are not intellective owning to abundant manual input. In this paper, we describe a semi-supervised ensemble technique based on adaboost classifiers in a co-training framework. In this way to detect shadows just demand a fraction of labled...
With the increasing of sudden cardiac death, the developing of a reliable and portable electrocardiograph (ECG) monitor is imminent, especially automated external defibrillators (AEDs). A pivotal component in AEDs is the detection of ventricular fibrillation (VF) by means of appropriate detection algorithms. Various algorithms were proposed, here we proposed a new algorithm, which is based on support...
Based on the clustering technology in data mining, we aimed to establish a new schoolwork identifying mechanism. In order to let the normal answer can adapt to actual situations better, we first generalized the normal answer, and then calculated the similarity between every sample and normal answer, as well as similar degree between school works. Based on the similarity, we clustered all school work...
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