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IEEE International Conference on Granular computing (GRC)

作者： Mingfen Wu Tao Chen School of Computer Science Wuyi University Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science Wuyi University China

Rough set theory and fuzzy set theory are complementary generalizations of classical set *** paper concerns with rough sets,fuzzy sets and vector *** construct a rough fuzzy sets model based on a congruence of a vector space and it is assumed that the knowledge about a vector space should be restricted by a ***, we research fuzzy subs paces of the vector space over a field, and get a series of properties. Specifically,we construct the minimum fuzzy subspace containing two fuzzy subspaces in a vector space. Secondly, we define concepts of the lower(upper) approximations of fuzzy subsets with respect to a subspace, and give some properties of the lower and the upper approximations of fuzzy subsets. Finally, we focus on fuzzy subspaces of the vector space, and define the lower(upper) rough fuzzy subspaces and the rough fuzzy subspaces of the vector space. We obtain that a fuzzy subspace is certainly a rough fuzzy subspace, the intersection and sum of two fuzzy subspaces are also rough fuzzy subs paces and other valuable results.

关键词： Educational institutions Vectors Fuzzy logic

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Activity recognition based on semantic spatial relation

Activity recognition based on semantic spatial relation

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International Conference on Pattern Recognition

作者： Lingxun Meng Laiyun Qing Peng Yang Jun Miao Xilin Chen Dimitris N. Metaxas University of the Chinese Academy of Sciences Beijing Beijing CN Computer Science Department Rutgers University Piscataway NJ USA Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

We propose an approach to recognize group activities which involve several persons based on modeling the interactions between human bodies. Benefitted from the recent progress in pose estimation [1], we model the activities as the interactions between the parts belong to the same person (intra-person) and those between the parts of different persons (inter-person). Then a unified, discriminative model which integrates both types of interactions is developed. The experiments on the UT-Interaction Dataset [2] show the promising results and demonstrate the power of the interacting models.

关键词： Joints Humans Semantics Testing Estimation Biological system modeling Image recognition

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STRUCTURED SPARSE LINEAR DISCRIMINANT ANALYSIS

STRUCTURED SPARSE LINEAR DISCRIMINANT ANALYSIS

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IEEE International Conference on Image processing

作者： Zhen Cui Shiguang Shan Haihong Zhang Shihong Lao Xilin Chen School of Computer Science and Technology Huaqiao University Xiamen China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Omron Social Solutions Company Limited Kyoto Japan

Linear Discriminant Analysis (LDA) is an efficient image feature extraction technique by supervised dimensionality reduction. In this paper, we extend LDA to Structured Sparse LDA (SSLDA), where the projecting vectors are not only constrained to sparsity but also structured with a pre-specified set of shapes. While the sparse priors deal with small sample size problem, the proposed structure regularization can also encode higher-order information with better interpretability. We also propose a simple and efficient optimization algorithm to solve the proposed optimization problem. Experiments on face images show the benefits of the proposed structured sparse LDA on both classification accuracy and interpretability.

关键词： Face Face recognition Databases Linear discriminant analysis Optimization Training Algorithm design and analysis

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Approximation operators based on vague relations and roughness measures of vague sets

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Frontiers of Computer Science 2011年第4期5卷 429-441页

作者： Mingfen WU Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Science Wuyi University Jiangmen 529020 China

Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy set model based on fuzzy relations to vague sets. We mainly focus on the lower and upper approxima- tion operators of vague sets based on vague relations, and investigate the basic properties of approximation opera- tors on vague sets. Specially, we give some essential characterizations of the lower and upper approximation operators generated by reflexive, symmetric, and transi- tive vague relations. Finally, we structure a parameterized roughness measure of vague sets and similarity measure methods between two rough vague sets, and obtain some properties of the roughness measure and similarity measures. We also give some valuable counterexamples and point out some false properties of the roughness measure in the paper of Wang et al.

关键词： vague relation vague approximation space,rough vague set roughness measure similarity measure

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A granularity attribute reduction method based on binary discernibility matrix

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International Journal of Advancements in computing Technology 2012年第12期4卷 213-221页

作者： Chang, Tong Shifei, Ding Hong, Zhu Hongjie, Jia Jian, Wang 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 Sciences Beijing 100190 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

At present, most of the attribute reduction algorithms based on granularity are simply computing the granularity of knowledge. Repeated calculation will increase the time complexity. Binary discernibility matrix is used to express binary form, which has a clear ascension whether in space or in time than the traditional discernibility matrix efficiency. On the basis of granularity-based attribute reduction, a method is proposed to preprocess the dataset by using binary discernibility matrix. Firstly, find the core attribute and a minimal reduction. Then use the granularity thought to calculate each particle of the importance of attributes. Most important is joined to the reduction set, thereby achieving the attributes reduction. The example analysis shows that the method can improve the performance of the traditional attribute reduction algorithms effectively. It is a feasible approach to reduce attributes.

关键词： Rough set theory

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A support vector extraction method based on clustering membership

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第13期6卷 1-10页

作者： Qi, Bingjuan Ding, Shifei Huang, Huajuan Yu, Junzhao Wang, Jian 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 100190 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

Traditional support vector machine has disadvantages of slow training speed and great time consumption when dealing with large-scale datasets. This paper proposes a support vector extraction method based on clustering membership, which preprocesses the training datasets and extracts all possible support vectors for SVM training according to the memberships. Considering the training datasets may be linear or nonlinear, this paper severally uses FCM and KFCM to extract support vectors. Experiment results show that the method proposed in this paper can improve the training speed greatly in the condition of maintaining the classification accuracy.

关键词： Support vector machines

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Image sets alignment for Video-Based Face Recognition

Image sets alignment for Video-Based Face Recognition

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zhen Cui Shiguang Shan Haihong Zhang Shihong Lao Xilin Chen School of Computer Science and Technology Huaqiao University Xiamen China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China Omron Social Solutions Company Limited Kyoto Japan

Video-based Face Recognition (VFR) can be converted to the matching of two image sets containing face images captured from each video. For this purpose, we propose to bridge the two sets with a reference image set that is well-defined and pre-structured to a number of local models offline. In other words, given two image sets, as long as each of them is aligned to the reference set, they are mutually aligned and well structured. Therefore, the similarity between them can be computed by comparing only the corresponded local models rather than considering all the pairs. To align an image set with the reference set, we further formulate the problem as a quadratic programming. It integrates three constrains to guarantee robust alignment, including appearance matching cost term exploiting principal angles, geometric structure consistency using affine invariant reconstruction weights, smoothness constraint preserving local neighborhood relationship. Extensive experimental evaluations are performed on three databases: Honda, MoBo and YouTube. Compared with competing methods, our approach can consistently achieve better results.

关键词： Manifolds Face Image matching Face recognition Image reconstruction Video sequences Computational modeling

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Twin support vector machines based on rough sets

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第20期6卷 493-500页

作者： Yu, Junzhao Ding, Shifei Jin, Fengxiang Huang, Huajuan Han, Youzhen 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 100190 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

TWSVM(Twin Support Vector Machines) is based on the idea of GEPSVM (Proximal SVM based on Generalized Eigenvalues), which determines two nonparallel planes by solving two related SVM-type problems, so that its computing cost in the training phase is 1/4 of standard SVM. In addition to keeping the superior characteristics of GEPSVM, the classification performance of TWSVM significantly outperforms that of GEPSVM. In order to further improve the speed and accuracy of TWSVM, this paper proposes the twin support vector machines based on rough sets. Firstly, using the rough sets theory to reduce the attributes, and then using TWSVM to train and predict the new datasets. The final experimental results and data analysis show that the proposed algorithm has higher accuracy and better efficiency compared with the traditional twin support vector machines.

关键词： Rough set theory

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The study on power quality evaluation based on data analysis

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International Journal of Advancements in computing Technology 2012年第19期4卷 586-592页

作者： Zhang, Li Jiang, Yongcheng Liu, Ning Zhang, Bao-Hua Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230601 China School of Electric Engineering and Automation Anhui University Hefei 230601 China Library of Hefei Normal University Hefei 230601 China School of Electronics and Information Engineering Anhui University Hefei 230601 China

Power quality is the guide to the power of equipment malfunction or cannot work normally voltage. Rapid use, to the electric power quality caused serious, destruction and pollution power quality, produce the voltage wave and so on many kinds of power quality problems, to the user and power supply party bring huge economic loss "at the same time to plan. Microprocessor as the core of the intelligent precision equipment to the electric power quality put forward higher requirement, how to effectively can quality problem, improve the quality of power become the electric power industry research hotspot and focus of power quality inspection Richard and improve the quality of power, the prerequisite and basis of only fast. The correct detection and recognition of the electrical energy to take the right management measures improve the quality of power;reduce the loss of power quality problems.

关键词： Power quality

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Relaxed cross-lingual projection of constituent syntax

Relaxed cross-lingual projection of constituent syntax

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Conference on Empirical Methods in Natural Language processing, EMNLP 2011

作者： Jiang, Wenbin Liu, Qun Lü, Yajuan Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)1937284115

We propose a relaxed correspondence assumption for cross-lingual projection of constituent syntax, which allows a supposed constituent of the target sentence to correspond to an unrestricted treelet in the source parse. Such a relaxed assumption fundamentally tolerates the syntactic non-isomorphism between languages, and enables us to learn the target-language-specific syntactic idiosyncrasy rather than a strained grammar directly projected from the source language syntax. Based on this assumption, a novel constituency projection method is also proposed in order to induce a projected constituent tree-bank from the source-parsed bilingual corpus. Experiments show that, the parser trained on the projected treebank dramatically outperforms previous projected and unsupervised parsers. © 2011 Association for Computational Linguistics.

关键词： Syntactics

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