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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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A Pseudoinverse Incremental Algorithm for Fast Training Deep Neural Networks with Application to Spectra pattern recognition

A Pseudoinverse Incremental Algorithm for Fast Training Deep...

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International Joint Conference on Neural Networks

作者： Ke Wang Ping Guo Qian Yin A-Li Luo Xin Xin School of Computer Science and Technology Beijing Institute of Technology Image Processing and Pattern Recognition Laboratory Beijing Normal University Key Laboratory of Optical Astronomy National Astronomical Observatories Chinese Academy of Sciences

ISBN: (纸本)9781509006212

Deep learning scheme has received significant attention during these years, particularly as a way of building hierarchical representations from unlabeled data for a variety of signal and information processing tasks. However, deep neural networks suffer from slow learning speed since most used training algorithms are based on variations of the gradient descent algorithms which require iterative optimization and thus are time-consuming. In addition, a series of control parameters need to be specified empirically which lacks of the theoretical guidance, and current learning algorithms for deep networks are not very suitable to incremental learning scenario. To address these issues, we propose a fast learning scheme in this paper. The basic idea of our approach is to pre-train basic units such as auto-encoders of the deep architecture in an analytical way without any iterative optimization procedure. This scheme is also extended to an incremental learning version. The experimental result shows the superiority of our approach over the state-of-the-art gradient descent based algorithms. To demonstrate the impact of our algorithm on complicated real world applications, we give an example of its performance in astronomical spectra pattern recognition.

关键词： astronomical spectra Spectra pattern recognition learning (artificial intelligence) recognition (Psychology) Neural network algorithms control parameter Optimization Procedure descent Fasting Functional training Road

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A real-time algorithm for train position monitoring using optical time-domain reflectometry

A real-time algorithm for train position monitoring using op...

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IEEE International Conference on Intelligent Rail Transportation (ICIRT)

作者： Adam Papp Christoph Wiesmeyr Martin Litzenberger Heinrich Garn Walter Kropatsch Digital Safety and Security Department Austrian Institute of Technology GmbH Vienna Austria Pattern Recognition and Image Processing group Vienna University of Technology Vienna Austria

ISBN: (纸本)9781509015566

We propose an algorithm which uses an optical time-domain reflectometer (OTDR) for real-time tracking of trains. OTDR sensing, often also termed distributed acoustical sensing (DAS), measures the Rayleigh backscattering of a light pulse along an optical fiber. The resulting signal provides information on local acoustic pressure at linearly spaced positions along the fiber. While different approaches for train tracking with DAS are described in the literature, the results have been evaluated only for short time recordings with few train crossings. In this paper we provide details on the tracking performance of a novel algorithm that finds and tracks trains over 15km. Furthermore, this is the first contribution that uses ground truth data to assess the performance of the method. For the evaluation two one hour recordings are used.

关键词： Monitoring Vibrations Optical fibers Sensors Backscatter Rail transportation Time measurement

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Data graph formulation as the minimum-weight maximum-entropy problem 10

Data graph formulation as the minimum-weight maximum-entropy...

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10th IAPR-TC-15 International Workshop on Graph-Based Representations in pattern recognition, GbRPR 2015

作者： De Sousa, Samuel Kropatsch, Walter G. Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria

ISBN: (纸本)9783319182230

Consider a point-set coming from an object which was sampled using a digital sensor (depth range, camera, etc). We are interested in finding a graph that would represent that point-set according to some properties. Such a representation would allow us to match two objects (graphs) by exploiting topological properties instead of solely relying on geometrical properties. The Delaunay triangulation is a common out off-the-shelf strategy to triangulate a point-set and it is used by many researchers as the standard way to create the so called data-graph and despite its positive properties, there are also some drawbacks. We are interested in generating a graph with the following properties: the graph is (i) as unique as possible, (ii) and as discriminative as possible regarding the degree distribution. We pose a combinatorial optimization problem (Min-Weight Max-Entropy Problem) to build such a graph by minimizing the total weight cost of the edges and at the same time maximizing the entropy of the degree distribution. Our optimization approach is based on Dynamic Programming (DP) and yields a polynomial time algorithm. © Springer International Publishing Switzerland 2015.

关键词： Combinatorial optimization

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Automatic hemorrhage detection in color fundus images based on gradual removal of vascular branches

Automatic hemorrhage detection in color fundus images based ...

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IEEE International Conference on image processing

作者： Lei Zhou Penglin Li Qi Yu Yu Qiao Jie Yang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Shanghai General Hospital Shanghai Jiao Tong University Shanghai China

Hemorrhages in color fundus images usually vary in size and shape, and some are even connected with the retinal vasculature such that they are often omitted by previous detection methods. In this paper, we propose a new method to deal with these problems. During the hemorrhage candidate extraction stage, dark regions and retinal vasculature are segmented out respectively. Their individual advantages are fused together into a binary image with good vascular continuity. Then the gradual removal of vascular branches is applied to generate hemorrhage candidates. In the classification stage, a SVM classifier using 49 features is trained to classify the candidates into hemorrhages and non-hemorrhages. The experiments on DIARETDB1 and DIARETDB0 show that our method achieves good performance on sensitivity and specificity, especially at lesion level.

关键词： Hemorrhaging image segmentation Lesions Retinal vessels image color analysis Feature extraction

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image Guided Surgery System for Abdominal Aortic Aneurysm Operation

Image Guided Surgery System for Abdominal Aortic Aneurysm Op...

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2016 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics(AMEII 2016)

作者： Ming Niu Yajun Wu Lisheng Wang Chaoyi Cui Institute of Image Processing and Pattern Recognition Department of AutomationShanghai Jiao Tong University The Ninth People's Hospital affiliated to Shanghai Jiao Tong University

ISBN: (纸本)9781510823808

Abdominal aortic aneurysm(AAA) is a local enlargement of the abdominal *** can bring 90% mortality rate when the aneurysm expands gradually until ***,the stent interventional procedure is an effective means of treating the disease,which requires clinicians clearly understand the anatomical structure of abdominal aorta and the *** order to reduce the measurement risk and enhance the safety of operation,an image guided surgery(IGS) system is applied into *** the system,surgeons can know exactly morphological structure about the lesions and extract concerned parameters during *** paper introduces how 3D models of the abdominal aorta and aneurysm are segmented and reconstructed from CT images,and how appropriate centerline path are extracted and used for internal virtual roaming in these 3D *** how tumor diameter is measured through cutting plane perpendicular to computed axis Clinical applications have shown that such IGS system is practical and helpful in the operation.

关键词： Abdominal aortic aneurysm segment reconstruct surgery planning

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Multi-view implicit transfer for person re-identification 40

Multi-view implicit transfer for person re-identification

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

作者： Xu, Wei Li, Yijun Gong, Chen Yang, Jie Institution of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

ISBN: (纸本)9781467369978

Implicit camera transfer (ICT), which models the multi-valued mappings between two specific and stationary cameras, is a descent solution for the person re-identification problem of the surveillance system. It has the properties of simplicity, computational efficiency and well utilizing negative training data. But it neglects the complementary relation between the descriptors of various views. And different appearance people have various most discriminative views among all the views, which are under diverse mappings. To tackle with this constraint, we model the multi-values mapping from different view independently, and fuse these transferring results of each view by LPBoost. Experimental results demonstrate that our scheme not only inherits most of the advantages (some sacrifice in speed, but still can run in real time for the same testing case in the ICT paper) of ICT but also obtains more discriminative mappings than ICT. In addition, our solution gains competitive performance on 2 challenging datasets. © 2015 IEEE.

关键词： implicit camera transfer multi-view fusing person re-identification

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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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CONGENITAL HEART DISEASE (CHD) DISCRIMINATION IN FETAL ECHOCARDIOGRAM BASED ON 3D FEATURE FUSION

CONGENITAL HEART DISEASE (CHD) DISCRIMINATION IN FETAL ECHOC...

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IEEE International Conference on image processing

作者： Liqun Ji Yun Gu Kun Sun Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Division of Pediatric Cardiology Xin Hua Hospital School of Medicine Shanghai Jiao Tong University

ISBN: (纸本)9781467399623

Automatic diagnosis for fetal echocardiography plays an important part in diagnostic aid in the discrimination of congenital heart disease (CHD). Instead of traditional methods analyzing 2D cardiac echo video that need to find the standard view for discrimination, in this paper, we proposed a new system for automatic discrimination of CHD applying 4D original echocardiogram, which avoids the challenging work of searching standard views. We extracted the features of 3D static structure and 3D motion via 3D SIFT and 3D Histogram of Optical Flow (HOF) from the original 4D (3D+T) echocardiogram data, respectively. Bag of Words (BoW) method was employed to construct the quantized feature. Both static and motion features were fused to form the final image representation. One-Class SVM classifier was utilized to discriminate CHD due to the lack of CHD data and the significant difference in all the CHD cases. Experiments on the real data demonstrate the improved discrimination accuracy due to the fused feature.

关键词： Three-dimensional displays Feature extraction Support vector machines Heart Standards Training Optical imaging

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Motion Multi-object Detection Method under Complex Environment

Motion Multi-object Detection Method under Complex Environme...

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International Conference on Industrial Informatics, Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII)

作者： Zi-Xiao Pan Mei Wang School of Automation Wuhan University of Technology Wuhan China Yantai Vocational College Laboratory of Image Processing &Pattem Recognition Yantai China

ISBN: (纸本)9781509035762

An optimization object detection method based on color image symmetrical frame-difference is proposed in order to solve the problem of motion multi-object detection difficult under complex environment. In this paper, firstly the color images distance is defined to calculate the frame-difference between two adjacent images. Then the before and after symmetrical image-distance of three adjacent images in difference frame interval step can be completed respectively. Secondly, an optimization binary method is designed to extract more object pixels. And the before and after object binary results of the adjacent images with the same middle (key frame) image are given respectively. At last, motion multi-object of the key frame image is achieved by the fusion result of logical AND between the before and after object binary results depending on three-frame-adjacent images with the same key frame. Actual color images from traffic surveillance system are used to test, the experimental result shows that the optimization object detection algorithm based on symmetrical frame difference in the proper step can extract motion multi-objects in different movement speed under complex environment and its accuracy and effectiveness of the proposed algorithm are verified.

关键词： Object detection Color image edge detection Optimization Surveillance Traffic control Motorcycles

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