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A Novel Fast Support Vector Machine Based on Support Vector Geometry Analysis
基于几何分析的支持向量机快速训练与分类算法

HU Zheng-ping,WU Yan,ZHANG Ye,
胡正平
,吴燕,张晔

中国图象图形学报 , 2007,
Abstract: Support vector machine,a research hotspot of the pattern recognition in recent years,performs successfully in solving the nonlinear and high dimensional problems.However,training a support vector machine is equivalent to solving a linearly constrained quadratic programming problem in a number of variables equal to the number of data points.This optimization problem is known to be challenging when existing large number of training data points.Also,it is well known that the number of support vector plays an important role in the classification speed of SVM.So the method of pre-analysis efficient support vectors are used to train classifier becomes a novel task in SVM fields.In this paper,on the basis of a deep investigation into the geometry principle of support vectors and its distribution,we firstly pick out some neighbor vectors by nearest interclass distance analysis,and then select the margin vector by computing its intermixed factor of the neighbor vectors.So this method speeds up the SVM training and classifying synchronously by reducing the number of training samples and trimming the intermixed samples,while the ability of SVM remains unchanged.
Hierarchy Optical Flow Based Semi-Automatic Spatial-Temporal Video Segmentation
基于层次光流的半自动时空视频分割技术

ZHAO Ming,CHEN Chun,WU Zheng-ping,
赵明
,陈纯,邬正平

中国图象图形学报 , 2002,
Abstract: In the new MPEG-4 video coding standard, the semi-automatic video segmentation plays a key role in supporting object-oriented coding and enabling content-based functionalities. A novel hierarchy optical flow based semi-automatic spatial-temporal video segmentation method is presented in this paper. The proposed algorithm comprises of spatial and temporal segmentation modules. In the spatial segmentation stage, the user can input points around the video object(VO) with the proposed point-based graphic user interface(PBGUI), then active contour model and tracking bug algorithm are used to precisely define the video object of interest to be segmented. With the result of spatial segmentation, the temporal segmentation involves non-rigid object boundary tracking and rigid object whole entity tracking by hierarchy optical flow algorithm based on the algorithm proposed by Lucas and Kanade. And the tracking points selection algorithm is proposed to greatly improve the tracking performance in the rigid object whole entity tracking. The experimental results show that the proposed algorithm can precisely segment video objects from video clips and can be applied to object-oriented coding, content-based functionality and multimedia database indexing.
Research of USB Device Driver in Linux
Linux中USB设备驱动程序研究

LIANG Zheng-ping,WU Guo-qing,XIAO Jing,
梁正平
,毋国庆,肖敬

计算机应用研究 , 2004,
Abstract: Introduces some related concepts of USB and the pattern,data structures in Linux USB device driver.The general method and skill in Linux USB device driver are concluded by design and implement a representative example.
Research on simulation of virus propagation and control in scale-free networks
病毒在无标度网络上的传播及控制仿真研究*

LI Tao,GUAN Zhi-hong,WU Zheng-ping,
李涛
,关治洪,吴正平

计算机应用研究 , 2007,
Abstract: 网络病毒的爆发给计算机用户带来巨大的损失,同时互联网被认为是无标度网络,因此研究病毒在无标度网络上的传播及控制很有意义。通过构建一个BA无标度网络模型,对病毒的传播行为及影响因素进行了仿真分析。研究表明,采取恰当的策略可以有效地控制、预防病毒传播。
Research on Integration Process of Viewpoints in Viewpoint-oriented Requirements Engineering
多视点需求工程中视点集成过程的研究

LIANG Zheng-ping,MING Zhong,WU Guo-qing,
梁正平
,明仲,毋国庆

计算机科学 , 2009,
Abstract: The requirements information of all kinds of stakeholders is acquired and expressed using the form of viewpoint independently and dispersedly in Viewpoint-Oriented Requirements Engineering.It must integrate all of these viewpoints in order to yield an uniform specification.In this paper,the common development of viewpoints' specification was treated as the style of integration.The process of integration was modeled using the Category Theory.At the same time,this paper proposed two kinds of integration of vi...
Evaluating the AS-level Internet models: beyond topological characteristics

Fan Zheng-Ping,

中国物理 B , 2012,
Abstract: A surge number of models has been proposed to model the Internet in the past decades. However, the issue on which models are better to model the Internet has still remained a problem. By analysing the evolving dynamics of the Internet, we suggest that at the autonomous system (AS) level, a suitable Internet model, should at least be heterogeneous and have a linearly growing mechanism. More importantly, we show that the roles of topological characteristics in evaluating and differentiating Internet models are apparently over-estimated from an engineering perspective. Also, we find that an assortative network is not necessarily more robust than a disassortative network and that a smaller average shortest path length does not necessarily mean a higher robustness, which is different from the previous observations. Our analytic results are helpful not only for the Internet, but also for other general complex networks.
Preface

HAO Zheng-ping,

环境科学 , 2011,
Abstract:
Research on Software Architecture Evaluation Methods
软件体系结构评估方法的研究*

HU Hong-lei,WU Guo-qing,LIANG Zheng-ping,LIU Qiu-hua,
胡红雷
,毋国庆,梁正平,刘秋华

计算机应用研究 , 2004,
Abstract: The architecture evaluation of a software system has become more and more important to guarantee the final quality of the system.The purpose of evaluation is to identify the potential risks of the architecture and to verify the quality requirements addressed in the design.This paper presents three mature evaluation methods (SAAM,ATAM,ALPSM) firstly,then compare them in a conceptive framework to find the similarities and differences between these three methods.In the last discusses the combination of multiple methods,the reuse in evaluating the architecture,the introduction of evaluation to design and use in practice.
Research on integration of viewpoints based on increasement
基于递增方式的视点集成研究

LIANG Zheng-ping,MING Zhong,WU Guo-qing,WANG Zhi-qiang,
梁正平
,明仲,毋国庆,王志强

计算机应用研究 , 2008,
Abstract: 针对与视点集成相关的问题,首先讨论了基于开发关系的视点集成方式,然后提出了一种基于二元递增方式的视点集成过程;同时采用范畴理论对该集成过程进行了建模,有利于一般意义上进一步研究与视点集成相关的基本性质.
Occluded Face Recognition Based on Double Layers Module Sparsity Difference
Shuhuan Zhao,Zheng-ping Hu
Advances in Electronics , 2014, DOI: 10.1155/2014/687827
Abstract: Image recognition with occlusion is one of the popular problems in pattern recognition. This paper partitions the images into some modules in two layers and the sparsity difference is used to evaluate the occluded modules. The final identification is processed on the unoccluded modules by sparse representation. Firstly, we partition the images into four blocks and sparse representation is performed on each block, so the sparsity of each block can be obtained; secondly, each block is partitioned again into two modules. Sparsity of each small module is calculated as the first step. Finally, the sparsity difference of small module with the corresponding block is used to detect the occluded modules; in this paper, the small modules with negative sparsity differences are considered as occluded modules. The identification is performed on the selected unoccluded modules by sparse representation. Experiments on the AR and Yale B database verify the robustness and effectiveness of the proposed method. 1. Introduction Image recognition, especially face recognition, has attracted a lot of researchers due to its wide application. And many methods have been proposed to solve this problem, including PCA, LDA, SVM, and other related methods. Recently, sparse representation- (or coding-) based classification (SRC) is attracting more and more attention [1–3] and has gained great success in face recognition. Based on sparse representation, Qiao et al. propose sparsity preserving projections (SPP) [4] for unsupervised dimensionality reduction. It can preserve the sparse reconstructive weights and the application on the face recognition verifies the effective SPP. Although these methods perform well under some controlled conditions, they fail to perform well in the situation when test data is corrupted due to occlusion. To solve this problem, Wanger et al. proposed to solve the problem in paper [5] by extending training samples using the difference between samples. And paper [6] used the image Gabor-features for SRC, which can get a more compact occlusion dictionary; as a result, the computation complexity and the number of atoms were reduced. In addition, paper [7] proposed a novel low-rank matrix approximation algorithm with structural incoherence for robust face recognition. In this paper the raw training data was decomposed into a low-rank matrix and the sparse error matrix. Besides, it introduced structural incoherence between low-rank matrices which promoted the discrimination between different classes, and thus this method exhibits excellent discriminating ability.
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