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检索条件"任意字段=6th IAPR International Conference on Pattern Recognition in Bioinformatics"

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Bio-inspired computer visual system using GPU and Visual pattern Assessment Language (ViPAL): Application on breast cancer prognosis

Bio-inspired computer visual system using GPU and Visual Pat...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 international Joint conference on Neural Networks, IJCNN 2010

作者： Huang, Chao-Hui Racoceanu, Daniel Roux, Ludovic Putti, thomas C. Bioinformatics Institute School of Computing National University of Singapore Singapore Singapore France Université Joseph Fourier Grenoble France Department of Pathology National University Hospital Singapore Singapore

ISBN: (纸本)9781424469178

Bio-inspired computer vision is an emerging field. It aims to reproduce the capabilities of biological vision systems, eventually to simulate the visual functions for various purposes. In this paper, we propose a bio-inspired computer visual system using Graphical Processing Unit (GPU), and its application on breast cancer prognosis. the system extracts visual features from an input image using a mechanism which is similar to human visual system. then classify the visual features using a machine learning algorithm. As a result, the elements of the input image, which might be related to particular knowledge concepts, can be identified. © 2010 IEEE.

关键词： Diseases

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Mandarin stress detection using hierarchical model based boosting classification and regression tree

Mandarin stress detection using hierarchical model based boo...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 international Joint conference on Neural Networks, IJCNN 2010

作者： Ni, Chong-Jia Liu, Wen-Ju Xu, Bo National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424469178

Automatic stress detection is important for both speech understanding and natural speech synthesis. In this paper, we develop hierarchical model based boosting classification and regression tree (CART) to detect Mandarin stress by using acoustic evidence and text information. When comparing with previous proposed method at the same training and test sets, there are 2.52% and 1.09% absolute accuracy rate improvements respectively. We also analyze the differences between Mandarin stress detection and English pitch accent prediction, and prove some linguistic conclusions based on the large corpus in a different way. © 2010 IEEE.

关键词： Hierarchical systems

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recognition of abnormal vibrational responses of signposts using the two-dimensional geometric distance and Wilcoxon test

Recognition of abnormal vibrational responses of signposts u...

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international conference on Natural Language Processing and Knowledge Engineering

作者： Jinnai, Michihiro Akashi, Yukio Nakaya, Shinsuke Ren, Fuji Fukumi, Minoru Kagawa National College Takamatsu Kagawa Japan Nexco Engineering Ltd. Takamatsu Kagawa Japan University of Tokushima Tokushima Tokushima Japan

ISBN: (纸本)9781424468966

In expressway companies, workers have been impacting signposts using wooden hammers and estimating the degree of the corrosion by listening to the sound. In order to automate this, we have been developing software that recognizes an abnormal impact vibrational response due to corrosion. this software extracts sonograms from impact vibrational waves using the LPC spectrum analysis, and matches images of the sonogram between a standard and an input impact vibrations using the Two-dimensional Geometric Distance. then, the software distinguishes the abnormality of the input impact vibration using Wilcoxon rank-sum test. We have measured the impact vibrations of five normal signposts and five abnormal signposts, and carried out the automatic recognition experiments. As a result, the software has recognized correctly in all cases. We have verified the effectiveness of the proposed method. ©2010 IEEE.

关键词： pattern matching

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Study on the abnormal traffic status alarming based on the neural architecture

Study on the abnormal traffic status alarming based on the n...

引用

international conference on Natural Computation

作者： Zhu, Yin Traffic Management Engineering Department Chinese People's Public Security University Beijing China

ISBN: (纸本)9781424459612

this study creates an abnormal traffic status alarming method based on the neural architecture. the paper introduces the three layer BP (Back Propagation) neural network structure including the input layer, the hidden layer and the output layer. Each layer of the network will receive the input information from the upper layer of the network after which the crunodes will change the information by means of the non-linear mapped. therefore the changed information will be passed down to the next layer. Finally, there are several real examples on demonstrating the effectiveness of system algorithms. thereby travelers and traffic management units can better understand the impact of the existing incident. Based on the model effect assessments, this study shows that the proposed models are feasible in the Intelligent Transportation Systems (ITS) context. © 2010 IEEE.

关键词： pattern recognition

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Automatic panorama mosaicing with high distorted fisheye images

Automatic panorama mosaicing with high distorted fisheye ima...

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2010 6th international conference on Natural Computation, ICNC'10

作者： Xu, Yuanyuan Li, Xiaoming Tian, Yaping Lab. of Pattern Recognition Shanxi University Taiyuan China

ISBN: (纸本)9781424459612

Automatic construction of a full view panorama is an active area of research in the fields of photogrammetry, computer vision and computer graphics. Using fisheye camera for panorama generation could greatly reduce the number of images thanks to its wide field of view. A key step in creating panorama with fisheye camera is to estimate the cameras' motion parameters which are usually estimated by established correspondences. However, establishing correspondences is a difficult thing particularly for high distorted images. For this reason, most of the traditional systems based on fisheye cameras for creating panorama are only designed for some specific configurations such that correspondences can be easily established. In this paper, we try to give a more general solution to establishing correspondences for a fisheye image pair. First, the feature detector unaffected by the non-linear distortion (like the MSER-regions) is used to extract features in original image. then feature matching is realized on the virtual camera plane (VCP). Next the interested region is back-projected onto the VCP where it becomes a perspective one, so the standard affine invariant based matching algorithms can be employed directly. To combat data noise and improve the precision of the estimates of motion parameters, more correspondences are searched by applying guided matching strategy. Experiments showed that our algorithm can lead to the precise and reliable estimates and the final full view panorama is satisfactory. © 2010 IEEE.

关键词： Cameras

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Weigted-FP-tree based XML query pattern mining

Weigted-FP-tree based XML query pattern mining

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6th international conference on Advanced Data Mining and Applications, ADMA 2010

作者： Gu, Mi Sug Hwang, Jeong Hee Ho Ryu, Keun Database/BioInformatics Laboratory Chungbuk National University Korea Republic of Department of Computer Science Namseoul University Korea Republic of

ISBN: (纸本)3642173152

According as XML data have been prevailing in many areas such as internet and public documentation, we need to research data mining algorithm to XML data. And many kinds of techniques have been researched to speed up the query performance about XML data. In this paper, therefore, as the method for speeding up the query performance we analyze the XML query pattern and propose Weighted- FP-growth algorithm extracting the similar XML query pattern fast. the proposed method is applied to XML query subtrees. And we experimented our method compared with the existing algorithm. And we showed the proposed method outperform the other methods and give the fast query result to the repeatedly occurring queries. © 2010 Springer-Verlag.

关键词： XML

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An evaluation of neural network ensembles and model selection for time series prediction

An evaluation of neural network ensembles and model selectio...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 international Joint conference on Neural Networks, IJCNN 2010

作者： Barrow, Devon K. Crone, Sven F. Kourentzes, Nikolaos Department of Management Science Lancaster University Management School Lancaster LA1 4YX United Kingdom

ISBN: (纸本)9781424469178

Ensemble methods represent an approach to combine a set of models, each capable of solving a given task, but which together produce a composite global model whose accuracy and robustness exceeds that of the individual models. Ensembles of neural networks have traditionally been applied to machine learning and pattern recognition but more recently have been applied to forecasting of time series data. Several methods have been developed to produce neural network ensembles ranging from taking a simple average of individual model outputs to more complex methods such as bagging and boosting. Which ensemble method is best;what factors affect ensemble performance, under what data conditions are ensembles most useful and when is it beneficial to use ensembles over model selection are a few questions which remain unanswered. In this paper we present some initial findings using neural network ensembles based on the mean and median applied to forecast synthetic time series data. We vary factors such as the number of models included in the ensemble and how the models are selected, whether randomly or based on performance. We compare the performance of different ensembles to model selection and present the results. © 2010 IEEE.

关键词： pattern recognition

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A quantified sensitivity measure of radial basis function neural networks to input variation

A quantified sensitivity measure of radial basis function ne...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 international Joint conference on Neural Networks, IJCNN 2010

作者： Chen, Xianming Zeng, Xiaoqin Chu, Rong Zhong, Shuiming Institute of Pattern Recognition and Intelligent System Hohai University Nanjing 210098 China

ISBN: (纸本)9781424469178

the sensitivity of a neural network's output to its parameter variation is an important issue in both theoretical researches and practical applications of neural networks. this paper proposes a quantified sensitivity measure of the Radial Basis Function Neural Networks (RBFNNs) to input variation. the sensitivity is defined as the mathematical expectation of squared output deviations caused by input variations. In order to quantify the sensitivity, the input is treated as a statistical variable and a numerical integral technique is employed to approximately compute the expectation. Experimental verifications are run and the results show a very good agreement between the proposed sensitivity computation and computer simulation. the quantified sensitivity measure could be helpful as a general tool for evaluating RBFNNs' performance. © 2010 IEEE.

关键词： Radial basis function networks

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Study of Hand-Dorsa Vein recognition

Study of Hand-Dorsa Vein Recognition

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6th international conference on Intelligent Computing

作者： Wang, Yiding Li, Kefeng Cui, Jiali Shark, Lik-Kwan Varley, Martin N China Univ Technol Coll Informat Engn Beijing 100144 Peoples R China Univ Cent Lancashire Sch Comp Engn & Phys Sci Preston PR1 2HE Lancs England

ISBN: (纸本)9783642149214

A new hand-dorsa vein recognition method based on Partition Local Binary pattern (PLBP) is presented in this paper the proposed method employs hand-dorsa vein images acquired from a low cost near infrared device After preprocessing the image is divided into sub images LBP uniform pattern features are extracted from all the sub images which are combined to form the feature vector for token vein texture features the method is assessed using a similarity measure obtained by calculating the Chi square statistic between the feature vectors of the tested sample and the target sample Integral histogram method original LBP and Partition LBP with 16 32 64 sub-images are tested on a database of 2040 Images from 102 individuals built up by a custom-made acquisition device the experimental results show that Partition LBP performs better than original LBP Circular Partition LBP performs better than Rectangular Partition LBP and when the image was divided into 32 performs better than others

关键词： Biometrics hand dorsa vein Partition Local Binary pattern (PLBP)

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6th international conference on Advanced Data Mining and Applications, ADMA 2010

6th International Conference on Advanced Data Mining and App...

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6th international conference on Advanced Data Mining and Applications, ADMA 2010

ISBN: (纸本)9783642173127

the proceedings contain 118 papers. the special focus in this conference is on Advanced Data Mining and Applications. the topics include: Nearest neighbour distance matrix classification;classification inductive rule learning with negated features;fast retrieval of time series using a multi-resolution filter with multiple reduced spaces;DHPTID-HYBRID algorithm: A hybrid algorithm for association rule mining;an improved rough clustering using discernibility based initial seed computation;fixing the threshold for effective detection of near duplicate web documents in web crawling;topic-constrained hierarchical clustering for document datasets;discretization of time series dataset using relative frequency and k-nearest neighbor approach;MSDBSCAN: Multi-density scale-independent clustering algorithm based on DBSCAN;web users access paths clustering based on possibilistic and fuzzy sets theory;an efficient algorithm for mining erasable itemsets;discord region based analysis to improve data utility of privately published time series;Deep web sources classifier based on DSOM-EACO clustering model;kernel based K-medoids for clustering data with uncertainty;frequent pattern mining using modified cp-tree for knowledge discovery;spatial neighborhood clustering based on data field;surrounding influenced k-nearest neighbors: A new distance based classifier;a centroid k-nearest neighbor method;mining spatial association rules with multi-relational approach;an unsupervised classification method of remote sensing images based on ant colony optimization algorithm;discriminative Markov logic network structure learning based on propositionalization and χ2-Test;a novel clustering algorithm based on gravity and cluster merging;evolution analysis of a mobile social network;distance distribution and average shortest path length estimation in real-world networks;Weigted-FP-tree based XML query pattern mining.

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