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IEEE International Conference on Image Processing

作者： Xiaoyuan Jing Sheng Li David Zhang Jingyu Yang State Key Laboratory for Software Engineering Wuhan University of China Wuhan China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China College of Automation Nanjing University of Posts and Telecommunications China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong China College of Computer Science Nanjing University of Science and Technology of PLA China

Feature extraction is one of the most important problems in image recognition tasks. In many applications such as face recognition, it is desirable to eliminate the redundancy among the extracted discriminant features. In this paper, we propose two novel feature extraction approaches named local uncorrelated discriminant transform (LUDT) and weighted global uncorrelated discriminant transform (WGUDT) for face recognition, respectively. LUDT and WGUDT separately construct the local uncorrelated constraints and the weighted global uncorrelated constraints. Then they iteratively calculate the optimal discriminant vectors that maximize the Fisher criterion under the corresponding statistical uncorrelated constraints, respectively. The proposed LUDT and WGUDT approaches are evaluated on the public AR and FERET face databases. Experimental results demonstrate that the proposed approaches outperform several representative feature extraction methods.

关键词： Feature extraction Vectors Databases Face Face recognition Transforms

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年第PART 3期6677 LNCS卷

作者： Liu, Derong Zhang, Huaguang Polycarpou, Marios Alippi, Cesare He, Haibo Chinese Academy of Sciences Institute of Automation Key Laboratory of Complex Systems and Intelligence Science Beijing 100190 China Northeastern University College of Information Science and Engineering Shenyang Liaoing 110004 China University of Cyprus Dept. of Electrical and Computer Engineering 75 Kallipoleos Avenue 1678 Nicosia Cyprus Politecnico di Milano Dip. di Elettronica e Informazione Piazza L. da Vinci 32 20133 Milano Italy University of Rhode Island Dept. of Electrical Computer and Biomedical Engineering Kingston RI 02881 United States

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年第PART 1期6675 LNCS卷

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年第PART 2期6676 LNCS卷

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Class-imbalance learning based discriminant analysis

Class-imbalance learning based discriminant analysis

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Asian Conference on Pattern Recognition (ACPR)

作者： Xiaoyuan Jing Chao Lan Min Li Yongfang Yao David Zhang Jingyu Yang State Key Laboratory of Software Engineering Wuhan University of China Wuhan China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China College of Automation Nanjing University of Posts and Telecommunications Nanjing China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong China College of Computer Science Nanjing University of Science and Technology of PLA Nanjing China

Feature extraction is an important research topic in the field of pattern recognition. The class-specific idea tends to recast a traditional multi-class feature extraction and recognition task into several binary class problems, and therefore inevitably class imbalance problem, where the minority class is the specific class, and the majority class consists of all the other classes. However, discriminative information from binary class problems is usually limited, and imbalanced data may have negative effect on the recognition performance. For solving these problems, in this paper, we propose two novel approaches to learn discriminant features from imbalanced data, named class-balanced discrimination (CBD) and orthogonal CBD (OCBD). For a specific class, we select a reduced counterpart class whose data are nearest to the data of specific class, and further divide them into smaller subsets, each of which has the same size as the specific class, to achieve balance. Then, each subset is combined with the minority class, and linear discriminant analysis (LDA) is performed on them to extract discriminative vectors. To further remove redundant information, we impose orthogonal constraint on the extracted discriminant vectors among correlated classes. Experimental results on three public image databases demonstrate that the proposed approaches outperform several related image feature extraction and recognition methods.

关键词： Databases Feature extraction Vectors Correlation Handwriting recognition Training Educational institutions

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Training ANFIS system with DE algorithm

Training ANFIS system with DE algorithm

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Allahyar Z. Zangeneh Mohammad Mansouri Mohammad Teshnehlab Ali K. Sedigh Computer Engineering Department Science and Research Branch Islamic Azad university of Tehran Iran Intelligent System laboratory (ISLAB) Control Department K. N. Toosi University of Technology Tehran Iran Advanced Process Automation & Control laboratory (APAC) Control Department K. N. Toosi University of Technology Tehran Iran

In this study, a new type of training the adaptive network-based fuzzy inference system (ANFIS) is presented by applying different types of the Differential Evolution branches. The TSK-type consequent part is a linear model of exogenous inputs. The consequent part parameters are learned by a gradient descent algorithm. The antecedent fuzzy sets are learned by basic differential evolution (DE/rand/1/bin) and then with some modifications in it. This method is applied to identification of the nonlinear dynamic system, prediction of the chaotic signal under both noise-free and noisy conditions and simulation of the two-dimensional function. Instead of DE/rand/1/bin, this paper suggests the complex type (DE/current-to-best/1+1/bin & DE/rand/1/bin) on predicting of Mackey-glass time series and identification of a nonlinear dynamic system revealing the efficiency of proposed structure. Finally, the method is compared with pure ANFIS to show the efficiency of this method.

关键词： Vectors Adaptive systems Input variables Training Mathematical model Equations Firing

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Research of tourist attractions hotel QA system based on short message

Research of tourist attractions hotel QA system based on sho...

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作者： Mao, Cun-Li Yu, Zheng-Tao Xian, Yan-Tuan Guo, Jian-Yi Lei, Xiong-Li School of Information Engineering and Automation Kunming University of Science and Technology Kunming 650051 China Laboratory of Intelligent Information Processing Kunming University of Science and Technology Kunming 650051 China School of Computer Science and Technology Kunming College of Metallurgy Kunming 650093 China School of Architecture and Arts Kunming College of Metallurgy Kunming 650093 China

ISBN: (纸本)9789881725592

To the feature of service database of tourist attraction and hotel in tourism field,system framework and implementation of tourist attraction, hotel QA system based on short message is described, in which attraction and hotel information is stored in database. Attraction and hotel are defined as domain entity, entity property, property category and property value. According to the characteristics of short message, domain entity is identified by CRF;query topic (property category of domain entity) is identified by a dynamic assembly classification method for short text classification. In this method, a treelike assembly classifier was constructed to support the text classification. Further, a dynamic adjusting strategy was presented in the construction procedure and inverted index is built by Lucene. We use domain entity and query topic to search the corresponding answer, which is that extracting the property value corresponding to the entity property to achieve QA system of tourist attraction and hotel. Experimental results in Yunnan Tourist show that better result has been achieved;the proposed method increases the accuracy of QA system. © 2011 Chinese Assoc of Automati.

关键词： Hotels

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Characterizing, modeling, and simulating soft error susceptibility in cell-based designs in highly scaled technologies

Characterizing, modeling, and simulating soft error suscepti...

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European Conference on Radiation and its Effects on Components and Systems (RADECS)

作者： Y. F. Li M. Li J. Y. Zhao R. D. Schrimpf D. M. Fleetwood B. Zhang J. Q. Wang D. L. Wang Y. Wang Accelicon Technologies Inc. Cupertino CA USA Electrical Engineering and Computer Science Department Vanderbilt University Nashville TN USA State Key Laboratory of Electronic Thin Films and Integrated Devices University of Electronic Science and Technology Chengdu China Institute of Automation Chinese Academy of Sciences Beijing China Institute of Microelectronics Tsinghua University Beijing China

A systematic flow is described for characterizing, modeling, and simulating single event transient-induced soft errors in cell-based designs. Pulse broadening effects are quantified for a 65 nm CMOS process.

关键词： Boolean functions Data structures Pulse measurements Inverters Logic gates Delay SPICE

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Active Collision Avoidance Maneuver Design Under Constant Thrust ⋆

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IFAC Proceedings Volumes 2011年第1期44卷 9887-9892页

作者： Yongqiang Qi Yingmin Jia Junping Du Fashan Yu The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

Abstract In this paper, the relative position parameters of the target spacecraft are obtained by using the vision measurement and the target maneuver positions are calculated through the isochronous interpolation method. Furthermore, new switch control laws under constant thrust are designed for active collision avoidance maneuver of the chaser along a specified trajectory. The switch control laws are obtained based on the acceleration sequences and the working times of thrusters in three axes which can be respectively computed by the time series analysis method. The perturbations and fuel consumptions are addressed during the computation of the working times. The simulation results show that the constant thrust maneuver can effectively guarantee the chaser maneuvering along the specified trajectory.

关键词： Active collision avoidance maneuver Collision possibility Constant thrust Switch control laws

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Risk-Sensitive Cubature Filtering for Jump Markov Nonlinear Systems and Its Application to Land Vehicle Positioning ⋆

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IFAC Proceedings Volumes 2011年第1期44卷 20-25页

作者： Wenling Li Yingmin Jia Junping Du Fashan Yu The Seventh Research Division and the Department of Systems and Control Beihang University (BUAA) Beijing 100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics (LMIB) Ministry of Education SMSS Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

Abstract In this paper, a risk-sensitive filter for a class of jump Markov nonlinear systems is proposed. By using a set of weighted cubature points to approximate the intractable risk-sensitive recursions, the proposed filter could exhibit improved numerical stability with respect to the derivation of the square-root covariance, for which the unscented transform technique might halt the operations due to the presence of non-positive definite covariance. The performance of the proposed filter is illustrated through a simulation study of tracking a land vehicle with maneuvers.

关键词： Markov models Kalman filters estimation theory target tracking

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