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A discriminative model for traditional mongolian part of speech

A discriminative model for traditional mongolian part of spe...

引用

Chinese conference on pattern recognition

作者： Zhang, Guanhong Sloglo Odbal Department of Computer Science and Technology Key Lab of Network and Intelligent Information Processing Hefei University AnhuiHefei 230601 China Inner Mongolia University Inner Mongolia Hohhot 010021 China Hefei Institutes of Physical Science of Chinese Academy Siences AnhuiHefei 230001 China

ISBN: (纸本)9781424472109

This paper presents a discriminative model for part of speech tagging of traditional *** use Maximum Entropy Model with Morphological features of Mongolian. First, the context feature templates are defined and extracted from the training corpus. Then, the parameters of maximum entropy probability models are calculated. Experimental results show that integration of morphological features of Maximum Entropy Model for Mongolian part of speech tagging outperform HMM since they are flexible enough to capture many correlated non-independent features. ©2010 ieee.

关键词： Entropy

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p norm multiple kernel fisher discriminant analysis for object and image categorisation

p norm multiple kernel fisher discriminant analysis for obje...

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2010 ieee computer society conference on computer Vision and pattern recognition, CVPR 2010

作者： Yan, Fei Mikolajczyk, Krystian Barnard, Mark Cai, Hongping Kittler, Josef Centre for Vision Speech and Signal Processing University of Surrey Guildford Surrey GU2 7XH United Kingdom

ISBN: (纸本)9781424469840

In this paper, we generalise multiple kernel Fisher discriminant analysis (MK-FDA) such that the kernel weights can be regularised with an p norm for any p ≥ 1, in contrast to existing MK-FDA that uses either l1 or l2 norm. We present formulations for both binary and multiclass cases and solve the associated optimisation problems efficiently with semi-infinite programming. We show on three object and image categorisation benchmarks that by learning the intrinsic sparsity of a given set of base kernels using a validation set, the proposed p MK-FDA outperforms its fixed-norm counterparts, and is capable of producing state-of-the-art performance. Moreover, we show that our p MK-FDA outperforms the p multiple kernel support vector machine (p MK-SVM) which has been recently proposed. Based on this observation and our experience with single kernel FDA and SVM, we argue that the almost century-old FDA is still a strong competitor of the popular SVM. ©2010 ieee.

关键词： Support vector machines

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A patient-specific method for the evaluation of wall shear stress in human coronary arteries

A patient-specific method for the evaluation of wall shear s...

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32nd Annual International conference of the ieee Engineering-in-Medicine-and-Biology-society (EMBC 10)

作者： Salvucci, F. P. Perazzo, C. A. Gurfinkel, E. Armentano, R. L. Barra, J. G. Univ Favaloro Fac Ingn & Ciencias Exactas & Nat Dept Elect Buenos Aires DF Argentina Univ Favaloro Dept Fis & Quim Buenos Aires DF Argentina Fdn Favaloro Dept Ciencias Cardiovasculares Buenos Aires DF Argentina Univ Favaloro Dept Fisiol Buenos Aires DF Argentina

ISBN: (纸本)9781424441242

Atherosclerotic plaques form at specific sites of the arterial tree, an observation that has led to the "geometric risk factor" hypothesis for atherogenesis. It is accepted that the location of atherosclerotic plaques is correlated with sites subjected to low abnormal values of wall shear stress (WSS), which is in turn determined by the specific geometry of the arterial segment. In particular, the left coronary artery (LCA) is one of the most important sites of plaque formation and its progression may lead to stroke. However, little is known about hemodynamics and WSS distributions in the LCA. The purpose of this work is to set up a method to evaluate flow patterns and WSS distributions in the human LCA based on real patient-specific geometries reconstructed from medical images. A three-dimensional model of the LCA of a healthy patient was reconstructed based on a computer tomography (CT) study. A finite element volume mesh was constructed and blood flow trough it was modeled with the finite element method. WSS distribution was computed with later postprocessing. Results showed that the particular details of the geometry such as curvatures and branching produced flow disturbances and determined in last the WSS distribution. Specific regions of low WSS values were determined. This work shows the feasibility of developing a patient-specific method for evaluating flow pattern and WSS distributions in order to study atherosclerotic plaque formation in the human LCA with real geometries obtained from CT images processing.

关键词： arterial segment arterial tree atherogenesis atherosclerotic plaques blood flow blood vessels cardiovascular system computer tomography computerised tomography finite element method finite element volume mesh finite volume methods geometric risk factor haemodynamics haemorheology hemodynamics human coronary arteries image processing image reconstruction image reconstruction image segmentation left coronary artery medical image processing mesh generation patient-specific method three-dimensional model wall shear stress

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Development of computer graphics and digital image processing.applications on the iPhone

Development of computer graphics and digital image processin...

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23rd conference on Graphics, patterns and images Tutorials, SIBGRAPI-T 2010

作者： Fagundes, Luciano Godoy Santos, Rafael Programa de Pós-Graduação em Computação Aplicada Instituto Nacional de Pesquisas Espaciais São José Dos Campos São Paulo Brazil Lab. Associado de Computação e Matemática Aplicada Instituto Nacional de Pesquisas Espaciais São José Dos Campos São Paulo Brazil

ISBN: (纸本)9780769542331

The iPhone is one of the most powerful, complete and versatile portable phones on the market. There are presently more than 150.000 applications available for the iPhone, and its users had downloaded more than three billion applications so far. The iPhone have several capabilities that makes it an interesting platform for the development of applications that use image processing. computer graphics and/or pattern recognition algorithms: it is stable, popular, powerful, flexible and of course portable. What can a developer expect from the platform? What, in practical terms, can be done to implement those types of algorithms, and at what price? This survey paper (written as part of a short course presented at Sibgrapi' 2010) shows some concepts and practical issues on the developing of image processing. computer graphics and pattern recognition applications on the iPhone. Code snippets will be provided, and issues such as memory management, capabilities and limitations will be discussed. © 2010 ieee.

关键词： image processing

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Defects inspecting system for tapered roller bearings based on machine vision

Defects inspecting system for tapered roller bearings based ...

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International conference on Electrical and Control Engineering, ICECE 2010

作者： Wu, Qinghua Lou, Xunzhi Zeng, Zhen He, Tao Hubei Key Lab. of Modern Manufacture Quality Engineering School of Mechanical Engineering Hubei University of Technology Wuhan 430068 China

ISBN: (纸本)9780769540313

Many bearing manufacturers take traditional manual methods to inspect defects of bearings, which are in low efficiency, costly and unreliable. In this paper, a defects inspecting system for tapered roller bearing based on machine vision (DISTRB) is introduced. DISTRB is used to realize online automatic inspection, which includes mechanical parts, electrical parts, lighting equipments, a CCD, a computer and its software. DISTRB actualizes automatic online inspection by CCDs and defects recognizing algorithms and takes the place of workers' eyes. Some implementation devices are used to get high-quality images. Defects recognition algorithms of DISTRB are mainly elaborated. The defects of bearings include roller-missing in tapered roller bearings (RM) and some rollers being installed opposite to the direction of standard need (ROD). The key of DISTRB is to use practical image processing.skills to improve the accuracy of the defects recognizing algorithms. The accuracy and stability of DISTRB mainly depends on the algorithms with a precondition of a fixed lighting part and imaging part. The DISTRB involves multi-domains such as mechatronic engineering, computer science, image-processing.and pattern recognition. In this paper, taking image of type 32011X bearing as a research object, defects recognizing algorithms for RM and ROD defects are illustrated. After theoretical calculation and experiments in laboratory and practical applications in factories, the defects inspecting system is reliable, stable and effective. © 2010 ieee.

关键词： image recognition

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Brain tissue segmentation using an unsupervised clustering technique based on PSO algorithm

Brain tissue segmentation using an unsupervised clustering t...

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17th Iranian conference in Biomedical Engineering, ICBME 2010

作者： Azarbad, Milad Ebrahimzadeh, Ataollah Babajani-Feremi, Abbas Faculty of Electrical and Computer Engineering BABOL University of Technology Babol Iran Image Analysis Lab. Radiology Department Henry Ford Hospital Detroit United States

ISBN: (纸本)9781424474844

image thresholding is an important technique for image processing.and pattern recognition. Several thresholding techniques have been proposed in the literature. In this paper for segmentation of magnetic resonance images, a novel method using a combination of the multilevel thresholding algorithm and the hierarchical evolutionary algorithm (HEA) is proposed. The HEA can be viewed as a variant of conventional genetic algorithms. The proposed technique is based on the participle swarm optimization (PSO) and, in fact, is an unsupervised clustering method based on an automatic multilevel thresholding approach. One advantage of the proposed method is that the number of clusters in the given image does not need to be known in advance. We evaluate and validate performance of the proposed method using simulation studies. The simulation results show that the accuracy of the proposed method is about 96%. © 2010 ieee.

关键词： Magnetic resonance

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Architecture for binary mathematical morphology reconfigurable by genetic programming

Architecture for binary mathematical morphology reconfigurab...

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6th Southern Programmable Logic conference, SPL 2010

作者： Pedrino, Emerson Carlos Saito, José Hiroki Roda, Valentin Obac Department of Computer Science Federal University of São Carlos Rod. Washington Luís km235 SC SP CEP: 13565905 Brazil Department of Electrical Engineering University of São Paulo Av. Trabalhador São-carlense 400 SC SP CEP: 13566590 Brazil

ISBN: (纸本)9781424470891

Mathematical morphology supplies powerful tools for low level image analysis, with applications in robotic vision, visual inspection, medicine, texture analysis and many other areas. Many of the mentioned applications require dedicated hardware for real time execution. In this paper, the development of a novel reconfigurable hardware using logical and morphological instructions generated automatically by a linear approach based on genetic programming is proposed. The hardware is capable of processing.binary images at high speed. The developed system is based on high-capacity PLDs and has among the possible applications: automatic construction of image filters, intelligent pattern recognition, to name just a few. Some applications using the developed reconfigurable system are presented and the results are discussed and compared with other approaches. © 2010 ieee.

关键词： Genetic programming

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Watershed segmentation based on inertial product energy

Watershed segmentation based on inertial product energy

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Chinese conference on pattern recognition

作者： Ma, Jinwei Xue, Heru Su, Changming College of Computer and Information Engineering of Inner Mongolia Agricultural University Huhehaote 010018 China College of Information Science and Technology of Chengdu University Chengdu 610106 China

ISBN: (纸本)9781424472109

An image segmentation method is presented based on the inertial product energy to construct a good watershed structure for gradient level image and improve watershed segmentation. The inertial product energy can weaken the noises and tiny edges in gradient level image. Then a non-linear processing.classification and filtering based on fusion and adaptive are employed to reduce the influence of a lot of local minimum pixels which are less sensible in the inertial product energy image. Thus the inertial product energy image has a good watershed structure. Experimental results show that the proposed method significantly decrease the over-segmentation and provides a reliable basis for further processing. ©2010 ieee.

关键词： image segmentation

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Fast pattern matching using orthogonal Haar transform

Fast pattern matching using orthogonal Haar transform

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conference on computer Vision and pattern recognition (CVPR)

作者： Wanli Ouyang Renqi Zhang Wai-Kuen Cham Chinese University of Hong Kong New Territories Hong Kong China

pattern matching is a widely used procedure in signal processing. computer vision, image and video processing. Recently, methods using Walsh Hadamard Transform (WHT) and Gray-Code kernels (GCK) are successfully applied for fast transform domain pattern matching. This paper introduces strip sum on the image. The sum of pixels in a rectangle can be computed by one addition using the strip sum. Then we propose to use the orthogonal Haar transform (OHT) for pattern matching. Applied for pattern matching, the algorithm using strip sum requires O(log u) additions per pixel to project input data of size N × N onto u 2-D OHT basis while existing fast algorithms require O(u) additions per pixel to project the same data onto u 2-D WHT or GCK basis. Experimental results show the efficiency of pattern matching using OHT.

关键词： pattern matching Strips Signal processing.algorithms Video signal processing computer vision Tracking Vectors Kernel Video compression Application software

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A diffusion approach to seeded image segmentation

A diffusion approach to seeded image segmentation

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conference on computer Vision and pattern recognition (CVPR)

作者： Juyong Zhang Jianmin Zheng Jianfei Cai Nanyang Technological University Singapore

Seeded image segmentation is a popular type of supervised image segmentation in computer vision and image processing. Previous methods of seeded image segmentation treat the image as a weighted graph and minimize an energy function on the graph to produce a segmentation. In this paper, we propose to conduct the seeded image segmentation according to the result of a heat diffusion process in which the seeded pixels are considered to be the heat sources and the heat diffuses on the image starting from the sources. After the diffusion reaches a stable state, the image is segmented based on the pixel temperatures. It is also shown that our proposed framework includes the RandomWalk algorithm for image segmentation as a special case which diffuses only along the two coordinate axes. To better control diffusion, we propose to incorporate the attributes (such as the geometric structure) of the image into the diffusion process, yielding an anisotropic diffusion method for image segmentation. The experiments show that the proposed anisotropic diffusion method usually produces better segmentation results. In particular, when the method is tested using the groundtruth dataset of Microsoft Research Cambridge (MSRC), an error rate of 4.42% can be achieved, which is lower than the reported error rates of other state-of-the-art algorithms.

关键词： image segmentation Pixel Diffusion processes Anisotropic magnetoresistance Temperature computer vision image processing Error analysis Equations Process control

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