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In clutter background, the performance of tracking target can be influenced by the factors such as illumination, camera angle. Meanwhile the target can be occluded by some obstacles in the background or be occluded by the target itself. To solve those problems, a multi-window tracking method is proposed, which represents the tracking target with several windows that each one corresponds with a tracker...
For which low frequency discrete cosine transform (DCT) coefficients retransforming based on contrast limiting adaptive histogram equalization (CLAHE) is proposed. Firstly, original images are divided into several non-overlapping blocks and CLAHE is used to do local contrast stretching so as to reduce noise. Then, illustration variation of face image is removed by reducing suit numbers of low frequency...
With the wide application of embedded technology and its products, much attention has been turned to the development of program to improve the safety and reliability of embedded devices. In this paper, we present a construct program of embedded trusted computing environment based on QEMU virtual machine architecture. The proposed program, simulates functions of trusted cryptographic modules by software,...
Aiming at the problem of low accuracy in intrusion detection system, this paper established a genetic support vector machine (SVM) model according to the features of genetic algorithm and support vector machine algorithm. The model firstly optimizes the support vector parameters according to genetic algorithm, then we build the intrusion detection model with support vector machine optimized and use...
This paper presents an approach for classification which is based on the neighborhood expansion. The proposed algorithm can (1) find automatically the number of clusters, and (2) classify irregular data set. In the approach, we first defined the distance between a point and a set, then the neighborhood of a data set. The algorithm can begin with any point in the data set and expands the point to a...
In this article, a model migration strategy based on subspace separation is proposed for process monitoring by taking advantage of common information between an old process and a new process. Firstly, a global basis vector is extracted and deemed to enclose the cross-set similar correlations. Then two different subspaces are separated from each other in the new dataset. The kernel principal component...
Based on principal component analysis (PCA) and support vector machine (SVM), a new method for the fault diagnosis of TE Process is proposed. The fault recognition based on kernel principal component analysis (KPCA) is analyzed and SVM is employed as a classifier for fault classification. To establish a more efficient SVM model, genetic algorithm (GA) is used to determine the optimal kernel parameter...
This paper proposes a chaotic particle swarm optimization and kernel matching pursuit algorithm a combination of speaker recognition methods. First through the CPSO clustering algorithm to transform the MFCC feature parameters of processing, streamlining of the MFCC feature parameters (SMFCC), then use the KMP algorithm on the reduction parameters after the SMFCC feature classification training and...
Semantic relation extraction is an important part of information extraction, it has application value in the automatic question answering system, retrieval system, ontology learning, semantic web annotation, and many other areas. Pattern representation method is context pattern in previous semi-Supervised semantic relation extraction based on bootstrapping, but it did not consider the role of the...
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