检索结果-内蒙古大学图书馆

IEEE International Conference on Granular Computing (GRC)

作者： Meng Zuqiang Shi Zhongzhi Xu Ke College of Computer Electronics and Information Guangxi University Nanning China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

This paper systematically studies the problem of decision rule acquisition in inconsistent incomplete decision systems (IIDSs). First, a tolerance granular framework model based on tolerance granular computing is presented, which is suitable for variety types of decision rules in IIDSs; secondly, with the proposed model, a framework for acquiring all minimum decision rule sets for each type is given, which solves the problem of decision rule acquisition in IIDSs to a certain degree; finally, an example is given to show the efficiency of our framework.

关键词： Upper bound Computational modeling information systems Approximation methods Computers Educational institutions Knowledge acquisition

来源：评论

学校读者我要写书评

暂无评论

Visual saliency detection by spatially weighted dissimilarity

Visual saliency detection by spatially weighted dissimilarit...

引用

作者： Duan, Lijuan Wu, Chunpeng Miao, Jun Qing, Laiyun Fu, Yu College of Computer Science and Technology Beijing University of Technology Beijing 100124 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Science and Engineering Graduate University Chinese Academy of Sciences Beijing 100049 China Department of Computing University of Surrey Guildford Surrey GU2 7XH United Kingdom

ISBN: (纸本)9781457703942

In this paper, a new visual saliency detection method is proposed based on the spatially weighted dissimilarity. We measured the saliency by integrating three elements as follows: the dissimilarities between image patches, which were evaluated in the reduced dimensional space, the spatial distance between image patches and the central bias. The dissimilarities were inversely weighted based on the corresponding spatial distance. A weighting mechanism, indicating a bias for human fixations to the center of the image, was employed. The principal component analysis (PCA) was the dimension reducing method used in our system. We extracted the principal components (PCs) by sampling the patches from the current image. Our method was compared with four saliency detection approaches using three image datasets. Experimental results show that our method outperforms current state-of-the-art methods on predicting human fixations. © 2011 IEEE.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

A fuzzy support vector machine algorithm with dual membership based on hypersphere

引用

Journal of Computational information Systems 2011年第6期7卷 2028-2034页

作者： Ding, Shifei Gu, Yaxiang School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China

In traditional fuzzy support vector machine(FSVM), membership function is established in global scope will reduce the membership of support vectors, and the FSVM based dismissing margin increases the training speed, but will remove some support vector artificially. So, a new algorithm of Fuzzy Support Vector Machine with Dual Membership based on Hypersphere (HDM-FSVM) is proposed. In this algorithm, the two classes of hyperspheres are divided into two parts respectively. Then, according to most support vectors are in the hemispheres which close together, we use the membership function that can enhance the membership of support vector, and because of there are a few of support vectors in other hemispheres, we must ensure the high membership of support vectors and reduce the membership of non-support vector. In order to removal noise and outliers, we introduce a radius controlling factor to control size of hyperspheres, the samples that outside of hyperspheres are considered as noise and outliers. Experimental results show that HDM-FSVM can enhance the classification accuracy rate of the sample sets that contain noise and outliers. Copyright © 2011 Binary information Press.

关键词： Membership functions

来源：评论

学校读者我要写书评

暂无评论

Quantum Immune Clonal Selection Algorithm for Multi-objective 0/1 Knapsack Problems

引用

Chinese Physics Letters 2010年第1期27卷 37-40页

作者：尚荣华焦李成李阳阳吴建设 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071

Based on the concept and principles of quantum computing and the principle of the immune clonal selection, a new algorithm for multi-objective 0/1 knapsack problems is introduced. In the algorithm, for the novel representation, qubit antibodies in the antibody population are updated by applying a new chaos update strategy. A quantitative metric is used for testing the convergence to the Pareto-optimal front. Simulation results on the 0/1 knapsack problems show that the new algorithm, in most cases, is more effective.

关键词： Chinese climate network complex systems small world community

来源：评论

学校读者我要写书评

暂无评论

DH-TRIE frequent pattern mining on Hadoop using JPA

DH-TRIE frequent pattern mining on Hadoop using JPA

引用

2011 IEEE International Conference on Granular Computing, GrC 2011

作者： Yang, Lai Shi, Zhongzhi Xu, Li D. Liang, Fan Kirsh, Ilan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China Dept. of ITDS Old Dominion University Norfolk VA 23529 United States Academic College of Tel-Aviv Yaffo Israel

ISBN: (纸本)9781457703713

The FPgrowth is a famous frequent pattern's algorithm in data mining when working with high-dimensional, large-scale data sets. It is also known as great complexity on memory for the recursively processing. In general, FPgrowth cannot handle large-scale data set unless dividing a whole data set into small blocks. Based on Hadoop, the open cloud computing model, a distributed DH-TRIE frequent pattern algorithm using JPA is proposed, which solved the three problems (globalization, random-write and duration). The algorithm is shown good flexibility and scalability by comparisons to mahout project. By applied to a virtualization platform Vega Cloud, the algorithm will be used in far-ranging situations. © 2011 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Fast common visual pattern detection via radiate geometric model

Fast common visual pattern detection via radiate geometric m...

引用

IEEE International Conference on Image processing

作者： Lingyang Chu Shuqiang Jiang Qingming Huang Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences China Institute of Computing Technology CAS Beijing China Chinese Academy of Sciences Beijing China

In this paper, we propose a novel method to implement fast detection of Common Visual Pattern (CVP). The purpose of CVP detection is to find the correspondences between the common visual regions of two given partial duplicate images. There are two major components of the proposed method which guarantee the good performance. First, we establish the Radiate-Geometric-Model (RGM). The RGM is represented by a set of radiate structures, and each structure is geometrically made up of a group of matched feature pairs. By utilizing the statistical information gained from the radiate structures, the RGM can not only quickly estimate the potential pairs of common regions but also organize the scale relationship between matched pairs into a compact form, hence increase the detection speed substantially. Second, we formulize the Radiate-Geometric-Model (RGM) into a graph optimization problem which could be solved by the method of graph-shift, thus make our algorithm capable of detecting the CVPs of all kinds of correspondences. Experimental results prove that the speed of our algorithm is at least 40 times faster than the state-of-the-art, while achieving a better detection performance at the same time.

关键词： Accuracy Histograms Visualization Optimization Feature extraction Conferences Vectors

来源：评论

学校读者我要写书评

暂无评论

An immune memory clonal algorithm for numerical and combinatorial optimization

引用

中国计算机科学前沿 2010年第4期4卷 536-559页

作者： Ruochen LIU Licheng JIAO Yangyang LI Jing LIU Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information ProcessingXidian UniversityXi'an 710071China

Inspired by the clonal selection theory together with the immune network model, we present a new artificial immune algorithm named the immune memory clonai algorithm (IMCA). The clonal operator,inspired by the immune system, is discussed first. The IMCA includes two versions based on different immune memory mechanisms; they are the adaptive immune memory clonal algorithm (AIMCA) and the immune memory clonal strategy (IMCS). In the AIMCA, the mutation rate and memory unit size of each antibody is adjusted dynamically. The IMCS realizes the evolution of both the antibody population and the memory unit at the same time. By using the clonal selection operator, global searching is effectively combined with local *** to the antibody-antibody (Ab-Ab) affinity and the antibody-antigen (Ab-Ag) affinity, The IMCA can adaptively allocate the scale of the memory units and the antibody population. In the experiments, 18 multimodal functions ranging in dimensionality from two, to one thousand and combinatorial optimization problems such as the traveling salesman and knapsack problems (KPs)are used to validate the performance of the IMCA. The computational cost per iteration is presented. Experimental results show that the IMCA has a high convergence speed and a strong ability in enhancing the diversity of the population and avoiding premature convergence to some degree. Theoretical roof is provided that the IMCA is convergent with probability 1.

关键词： artificial immune system (AIS) clonal selection immune memory immune network model evolutionary computation knapsack problem(KP) traveling salesman problem(TSP)

来源：评论

学校读者我要写书评

暂无评论

Fault pattern classification using modified dempster-shafer(D-S) combination rule

引用

Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis 2011年第2期31卷 144-149页

作者： Su, Xiaoyan Deng, Yong Wu, Ying Jiang, Wen School of Electronics Information and Electric Engineering Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Digital Agricultural Early-Warning Technology of Ministry of Agriculture Beijing 100081 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China College of Computer and Information Sciences Southwest University Chongqing 400715 China School of Electronics and Information Technology Northwestern Polytechnical University Xi'an 710072 China

A modified method of conventional D-S evidence combination rule was presented. The consensus index of evidence based on distance measures of evidence was introduced into modifying the BPAs of hypotheses with the evidence sufficiency and evidence importance. By using the D-S combination and new decision rules, the different sets of BPAs for each hypothesis were calculated. A numerical example of the fault diagnosis is used to demonstrate the validity of the method by comparison with other methods.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

GPU based fast algorithm for tanner graph based image interpolation

GPU based fast algorithm for tanner graph based image interp...

引用

IEEE Workshop on Multimedia Signal processing

作者： Wei Lei Ruiqin Xiong Siwei Ma Luhong Liang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China Institute of Digital Media Peking University Beijing China

In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy effect compared with other adaptive methods such as NEDI, SAI. Tanner graph based image interpolation algorithm has better effect in dealing with edge and texture, but with high computation complexity. Thanks to the high performance parallel processing capability of today's GPU, use of complex algorithms for real time application is becoming possible. In this paper, we present a fast algorithm for tanner graph based image interpolation and it's implementation on GPU. In our algorithm, the image model training process of tanner graph based image interpolation is greatly simplified. Experimental results show that the GPU implementation can be more than 47 times as fast as the CPU implementation.

关键词： Graphics processing unit Interpolation Training Instruction sets Parallel processing Equations Image resolution

来源：评论

学校读者我要写书评

暂无评论

Image enhancement based on improved fractional differentiation

引用

Journal of Computational information Systems 2011年第1期7卷 257-264页

作者： Gao, Chaobang Zhou, Jiliu Zheng, Xiuqing Lang, Fangnian College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province Chengdu 610106 China School of Computer Science Sichuan University Chengdu 610064 China

In this paper, according to the development of the fractional differentiation and its applications in the modern signal processing, we improve the numerical calculation of fractional differentiation by piecewise quadratic interpolation equation, that is, improved fractional differentiation, IFD for short, and propose a new corresponding operator, IFD operator. And we apply this new operator to image enhancement. Experiments show that, for texture-rich digital image, the capability of nonlinearly enhancing comprehensive texture details by IFD is very obvious. For quantity analysis, we particularly calculate the information entropy and average gradient. Comparing with fractional differentiation, the image obtained by IFD is clearer. © 2011 Binary information Press.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：