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第35届中国控制会议

作者： Penglin LI Yue LIU Yadong ZHAO Jie YANG Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University State Key Laboratory of Industrial Control Technology Institute of Industrial Process ControlCollege of Control Science and EngineeringZhejiang University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781509009107

In this paper,we discuss consensus problems for antagonistic networks with double integrator *** cases are analyzed:(1) undirected graphs with fixed topology on antagonistic networks;(2) undirected graphs with fixed topology and time-delay on antagonistic *** both cases,distributed consensus protocols are proposed,with sufficient and necessary conditions *** is proved that the largest tolerable time-delay is only related to the largest eigenvalue of the graph ***,simulations are provided to demonstrate the obtained theoretical results.

关键词： Consensus Fixed Topology Multi-agent Antagonistic Networks Time-delay

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First-principles study of the photovoltaic properties of orthorhombic Ca2Si1-xPx (0

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IOP Conference Series: Materials Science and Engineering 2017年第1期207卷

作者： Weifu Cen Yinye Yang Menghui Fan College of materials science and engineering Guizhou Minzu University Guiyang 550025 China Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province Guizhou Minzu University Guiyang 550025 China

Electronic structure and optical properties of simple orthorhombic Ca2Si1-xPx have been calcu-lated by the first-principles methods. The result shown that the band gap of the simple ortho-rhombic Ca2Si1-xPx was still a direct semiconductor and the band gap was increased with the concentration of P impurity increased. The dielectric constant and refractive index were in-creased with the concentration of P impurity increased. The extinction coefficient, the reflectivi-ty, the absorption and the conductivity have significant changed in the energy range of 0eV~1eV. Therefore, Transmission property of energy band structure and optical properties of simple or- thorhombic Ca2Si1-xPx were changed by changing the impurity concentration. It is a useful method for modulating photoelectric transmission property of the simple orthorhombic Ca2Si1-xPx.

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RGB-D saliency detection under Bayesian framework

RGB-D saliency detection under Bayesian framework

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International Conference on pattern recognition

作者： Song-Tao Wang Zhen Zhou Han-Bing Qu Bin Li Key Laboratory of Pattern Recognition Beijing Academy of Science and Technology Beijing China The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentations of Heilongjiang Province Harbin University of Science & Technology Harbin China

ISBN: (纸本)9781509048489

In this paper, we propose a saliency detection model for RGB-D images based on the contrasting features of color and depth within a Bayesian framework. The depth feature map is extracted based on superpixel contrast computation with spatial priors. We model the depth saliency map by approximating the density of depth-based contrast features using a Gaussian distribution. Similar to the depth saliency computation, the color saliency map is computed using a Gaussian distribution based on multi-scale contrasts in superpixels by exploiting low-level cues. By assuming that color- and depth-based contrast features are conditionally independent, given the classes, a discriminative mixed-membership naive Bayes (DMNB) model is used to calculate the final saliency map from the depth saliency and color saliency probabilities by applying Bayes' theorem. The Gaussian distribution parameter can be estimated in the DMNB model by using a variational inference-based expectation maximization algorithm. The experimental results on a recent eye tracking database show that the proposed model performs better than other existing models.

关键词： Feature extraction Computational modeling Solid modeling Three-dimensional displays Two dimensional displays Visualization Image color analysis

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Motion cue based pedestrian detection with two-frame-filtering

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High Technology Letters 2015年第3期21卷 328-332页

作者：吕敬钦 Zhang Miaohui Yang Jie Institute of Image Processing and Pattern Recognition Shanghai Jiaotong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China

This study proposes a motion cue based pedestrian detection method with two-trame-filtering （Tff） for video surveillance. The novel motion cue is exploited by the gray value variation between two frames. Then Tff processing filters the gradient magnitude image by the variation map. Summa- tions of the Tff gradient magnitudes in cells are applied to train a pre-deteetor to exclude most of the background regions. Histogram of Tff oriented gradient （HTffOG） feature is proposed for pedestrian detection. Experimental results show that this method is effective and suitable for real-time surveil- lance applications.

关键词： pedestrian detection two-frame-filtering （TFF） Tff magnitude vector （TffMV） Histogram of Tff oriented gradient （ HTffOG） SVM video surveillance

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Corrigendum to “Road detection algorithm for Autonomous Navigation Systems based on dark channel prior and vanishing point in complex road scenes” [Robot. Auton. Syst. 85 (2016) 1–11]

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Robotics and Autonomous Systems 2017年 88卷 202-202页

作者： Yong Li Weili Ding Xuguang Zhang Zhaojie Ju Laboratory of Pattern Recognition and Intelligent Systems Key Laboratory of Industrial Computer Control Engineering of Hebei Province Department of Automation Institute of Electrical Engineering Yanshan University Qinghuangdao Hebei 066004 China College of Information Science and Engineering Northeastern University Shenyang Liaoning 110004 China School of Computing University of Portsmouth PO1 3HE UK

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Patch-based Object Tracking via Locality-constrained Linear Coding

Patch-based Object Tracking via Locality-constrained Linear ...

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第35届中国控制会议

作者： Kunqi Gu Mingna Liu Tao Zhou Fanghui Liu Xiangjian He Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai Institute of Spaceflight Control Technology Infrared Detection Technology Research and Development Center China Aerospace Science and Technology Corporation School of Computing and Communications University of Technology The Key Laboratory of Ministry of Education for System Control and Information Processing

ISBN: (纸本)9781509009107

In this paper,the Locality-constrained Linear Coding(LLC) algorithm is incorporated into the object tracking ***,we extract local patches within a candidate and then utilize the LLC algorithm to encode these *** on these codes,we exploit pyramid max pooling strategy to generate a richer feature *** feature histogram which integrates holistic and part-based features can be more discriminative and ***,an occlusion handling strategy is utilized to make our tracker more ***,an efficient graph-based manifold ranking algorithm is exploited to capture the relevance between target templates and *** tracking,target templates are taken as labeled nodes while target candidates are taken as unlabeled nodes,and the goal of tracking is to search for the candidate that is the most relevant to existing labeled nodes by manifold ranking *** on challenging video sequences have demonstrated the superior accuracy and robustness of the proposed method in comparison to other state-of-the-art baselines.

关键词： object tracking LLC pyramid max-pooling local appearance model manifold ranking

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OUGENE： a disease associated over-expressed and under-expressed gene database

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Science Bulletin 2016年第10期61卷 752-754页

作者： Xiaoyong Pan Hong-Bin Shen Section for Animal Genetics Bioinformatics and Breeding Center for Non-Coding RNA in Technology and Health University of Copenhagen 1870 Frederiksberg Denmark Department of Disease Systems Biology Novo NordiskFoundation Center for Protein Research University ofCopenhagen 1870 Frederiksberg Denmark Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Gene over-expression or under-expression is closely associated with human diseases, which contributes to phenotypic variations and diversity. To our best knowledge, there is no single open specific resource available to provide the association information between gene over- or under-expression and various diseases. In this study, we presented a comprehensive disease-associated over- and under-expressed gene database （OUGene） based on our proposed text mining pipeline and several open curated databases. It contains total 41,269 unique associa- tions between 7,238 over- or under-expressed genes and 1,480 diseases, which are supported by 81,974 evidence sentences from 56,442 articles. The OUGene is compre- hensive and covers most important therapeutic areas. Meanwhile a new scoring system is designed to rank the associations based on benchmarking against hand-curated data. OUGene provides an easy-of-use web interface for researchers to analyze these data and visualize the associ- ated networks, which can give insights to the complex relationships between over- and under-expressed genes and diseases at a system level. It is available at ***. ***/bioinf/OUGene/.

关键词： Text mining Gene over- and under-expression Disease Database

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A glass image classification method based on multi-feature fusion

A glass image classification method based on multi-feature f...

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International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Liang Zhang Jing Wen Sheng-Zhou Xu Hao-Yang Xing Yu Zhu Heng-Xin Chen College of Computer Science Chongqing University Chongqing China Key Laboratory of Pattern Recognition and Intelligent Chengdu University China School of Computer Science South-central University For Nationalities WuHan China Magnetic Resonance Imaging Research Centre Huaxi Hospital Chengdu Sichuan China Chongqing University Chongqing Sichuan CN

ISBN: (纸本)9781509029181

In this work, a new glass classification method is proposed. Firstly, images are enhanced by image preprocessing. Secondly, a series of glass features including shape and texture features are proposed. Finally, we employ simple minimum distance classifier to classify the input glass images. The experimental results show that the proposed method has high classification efficiency and accuracy.

关键词： Glass pattern recognition Training Shape Wavelet analysis Sorting Production facilities

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The Practical Teaching Design of Recommendation System Based on Collaborative Filtering Algorithm

The Practical Teaching Design of Recommendation System Based...

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2015 2nd International Conference on Education Reform and Modern Management(ERMM2015)

作者： Panpan Liu Jianyi Guo Zhengtao Yu Yantuan Xian Cunli Mao Huafeng Li Kunming University of Science and Technology Key Laboratory of Pattern recognition And Intelligent computing of Yunnan College

ISBN: (纸本)9781510803138

In order to resolve the implementation about the decision support system in "Decision Analysis and Decision Support" course for postgraduates. We introduced the design of recommendation system into the teaching practice. This paper describes the principles of recommendation system based on the collaborative filtering algorithm and introduces the process of the system. Through the practice of a practical problem, students can realize a recommendation system and understand the process of the decision support system.

关键词： intelligent decision Recommendation system Collaborative filtering Practical teaching

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Small target detection using an optimization-based filter 40

Small target detection using an optimization-based filter

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Xie, Kai Fu, Keren Zhou, Tao Yang, Jie Wu, Qiang He, Xiangjian Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China School of Computing and Communications University of Technology Sydney Australia

ISBN: (纸本)9781467369978

Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter. © 2015 IEEE.

关键词： active area area statistics heavy clutter optimization-based filter small target detection

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