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3rd International Symposium on Plant Growth Modeling, Simulation, Visualization and Applications, PMA09

作者： Zhu, Chao Zhang, Xiaopeng Jaeger, Marc Wang, Yinghui Sino-French Laboratory LIAMA CAS Institute of Automation Beijing China National Laboratory of Pattern Recognition CAS Institute of Automation Beijing China CIRAD AMAP INRIA EPI DigiPlante Montpellier France Department of Computer Science and Engineering Xi'An University of Technology Xi'an China

ISBN: (纸本)9780769539881

It is a challenge task to reconstruct a real tree from scattered scanned points in virtual reality. Although many progresses have been made on main branch structures and overall tree shape, reconstructions are still not faithful in terms of silhouette and details. We push the idea that 3D reconstruction of the tree crown shapes may help to constrain reconstruction of complete real tree geometry. We propose here a new approach to reconstruct tree crown based on clusters of points, where the data are unevenly distributed points in a volume rather than lying on a surface. From this approach several extracted silhouette mesh models can be generated;every mesh model represents a crown section of the reconstructed tree crown. Experimental result shows that our technique works well on crown shape of real trees. © 2010 IEEE.

关键词： Virtual reality

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Incremental learning in nonstationary environments with controlled forgetting

Incremental learning in nonstationary environments with cont...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ryan Elwell Robi Polikar Signal Processing and Pattern Recognition Laboratory Electrical and Computer Engineering Department Rowan University Glassboro NJ USA

We have recently introduced an incremental learning algorithm, called Learn ++ .NSE, designed for Non-Stationary Environments (concept drift), where the underlying data distribution changes over time. With each dataset drawn from a new environment, Learn ++ .NSE generates a new classifier to form an ensemble of classifiers. The ensemble members are combined through a dynamically weighted majority voting, where voting weights are determined based on classifiers' age-adjusted accuracy on current and past environments. Unlike other ensemble-based concept drift algorithms, Learn ++ .NSE does not discard prior classifiers, allowing potentially cyclical environments to be learned more effectively. While Learn ++ .NSE has been shown to work well on a variety of concept drift problems, a potential shortcoming of this approach is the cumulative nature of the ensemble size. In this contribution, we expand our analysis of the algorithm to include various ensemble pruning methods to introduce controlled forgetting. Error or age-based pruning methods have been integrated into the algorithm to prevent potential out-voting from irrelevant classifiers or simply to save memory over an extended period of time. Here, we analyze the tradeoff between these precautions and the desire to handle recurring contexts (cyclical data). Comparisons are made using several scenarios that introduce various types of drift.

关键词： Neutron spin echo Algorithm design and analysis Voting

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Multiresolution multiscale active mask segmentation of fluorescence microscope images

Multiresolution multiscale active mask segmentation of fluor...

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Wavelets XIII

作者： Srinivasa, Gowri Fickus, Matthew Kovacevic, Jelena Department of Mathematics and Statistics Air Force Institute of Technology Wright-Patterson AFB OH 45433 United States Center for Bioimage Informatics Departments of Biomedical and Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA 15213 United States Center for Pattern Recognition Department of Information Science and Engineering PES School of Engineering Bangalore India

ISBN: (纸本)9780819477361

We propose an active mask segmentation framework that combines the advantages of statistical modeling, smoothing, speed and flexibility offered by the traditional methods of region-growing, multiscale, multiresolution and active contours respectively. At the crux of this framework is a paradigm shift from evolving contours in the continuous domain to evolving multiple masks in the discrete domain. Thus, the active mask framework is particularly suited to segment digital images. We demonstrate the use of the framework in practice through the segmentation of punctate patterns in fluorescence microscope images. Experiments reveal that statistical modeling helps the multiple masks converge from a random initial configuration to a meaningful one. This obviates the need for an involved initialization procedure germane to most of the traditional methods used to segment fluorescence microscope images. While we provide the mathematical details of the functions used to segment fluorescence microscope images, this is only an instantiation of the active mask framework. We suggest some other instantiations of the framework to segment different types of images. © 2009 SPIE.

关键词： Fluorescence microscopy

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Data preprocessing in SVM-based keywords extraction from scientific documents

Data preprocessing in SVM-based keywords extraction from sci...

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2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009

作者： Wu, Chunguo Marchese, Maurizio Wang, Yufei Krapivin, Mikalai Wang, Chaoyong Li, Xitong Liang, Yanchun College of Computer Science and Technology Jilin University Changchun 130012 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China Italy Department of Fundamental Sciences Jilin Teacher's Institute of Engineering and Technology Changchun 130021 China

ISBN: (纸本)9780769538730

Scientific documents are unstructured data consisting of natural language and hard for scientists to read and manage. Keywords are very helpful for scientists to search the related documents and know about their contents in a prompt way. In this paper we investigate a kind of data preprocessing technique used in SVM-based keyword extraction from scientific documents. Four definitions of regular scientific documents are proposed, and the analysis on the experimental results is performed based on the proposed definitions. The experimental results confirm the intuition that abstract is important for keywords extraction. © 2009 IEEE.

关键词： Support vector machines

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A Visual Impaired Simulator to achieve Embedded Accessibility Designs

A Visual Impaired Simulator to achieve Embedded Accessibilit...

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2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(ICIS2009)

作者： Konstantinos Votis Theofanis Oikonomou Peter Korn Dimitrios Tzovaras Spiridon Likothanassis Informatics and Telematics Institute 6th km Charilaou-Thermi RoadThessalonikiGR-57001 Greece Pattern Recognition Laboratory Computer Engineering and InformaticsUniversity of Patras RioPatrasGreece

The ever increasing of software technologies has brought closer technology to users with visual impaired *** diversification poses a real challenge to "authors" (developers and designers) when creating software that has to cope with a myriad of interaction situations,as well as specific directives for ensuring an accessible *** an advanced accessibility simulation tool,"authors" can obtain a better understanding of the accessibility constraints for visual impaired users within a Java Swing application by simulating each *** proposed NetBeans-enabled plugin tool will assist them,with a minimal effort,to explore user-centered design and important accessibility issues for their Java Swing implementations

关键词： Human computer Interaction,Web Accessibility,Simulation,software design,User-centered design

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Modeling the MagnetoencephaloGram (MEG) Of Epileptic Patients Using Genetic Programming and Minimizing the Derived Models Using Genetic Algorithms

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AIP Conference Proceedings 2009年第1期1168卷 486-488页

作者： Konstantinos Theofilatos Efstratios Georgopoulos Spiridon Likothanassis aPattern Recognition Laboratory Department of Computer Engineering and Informatics University of Patras 265 00 Patras Hellas bTechnological Educational Institute of Kalamata Kalamata Hellas

In this paper, a variation of traditional Genetic Programming(GP) is used to model the MagnetoencephaloGram(MEG) of Epileptic Patients. This variation is Linear Genetic Programming(LGP). LGP is a particular subset of GP wherein computer programs in population are represented as a sequence of instructions from imperative programming language or machine language. The derived models from this method were simplified using genetic algorithms. The proposed method was used to model the MEG signal of epileptic patients using 6 different datasets. Each dataset uses different number of previous values of MEG to predict the next value. The models were tested in datasets different from the ones which were used to produce them and the results were very promising.

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Adaptive kernel principal analysis for online feature extraction

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World Academy of Science, engineering and Technology 2009年 59卷 288-293页

作者： Ding, Mingtao Tian, Zheng Xu, Haixia Department of Science Northwestern Polytechnical University Xi'an China Department of Science Department of Computer Science and Engineering Northwestern Polytechnical University Xi'an China National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Department of Computer Science and Engineering Northwestern Polytechnical University Xi'an China

The batch nature limits the standard kernel principal component analysis (KPCA) methods in numerous applications, especially for dynamic or large-scale data. In this paper, an efficient adaptive approach is presented for online extraction of the kernel principal components (KPC). The contribution of this paper may be divided into two parts. First, kernel covariance matrix is correctly updated to adapt to the changing characteristics of data. Second, KPC are recursively formulated to overcome the batch nature of standard *** formulation is derived from the recursive eigen-decomposition of kernel covariance matrix and indicates the KPC variation caused by the new data. The proposed method not only alleviates sub-optimality of the KPCA method for non-stationary data, but also maintains constant update speed and memory usage as the data-size increases. Experiments for simulation data and real applications demonstrate that our approach yields improvements in terms of both computational speed and approximation accuracy.

关键词： Covariance matrix

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ERP based decision fusion for AD diagnosis across cohorts

ERP based decision fusion for AD diagnosis across cohorts

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Metin Ahiskali Deborah Green John Kounios Christopher M. Clark Robi Polikar Signal Processing and Pattern Recognition Laboratory Department of Electrical and Computer Engineering Rowan University Glassboro NJ USA Department of Psychology Drexel University Philadelphia PA USA Department of Neurology University of Pennsylvania Philadelphia PA USA

As the average life expectancy increases, particularly in developing countries, prevalence of neurodegenerative diseases has also increased. This trend is especially alarming for Alzheimer's disease (AD); as there is no cure to stop or reverse the effects of AD. However, recent pharmacological advances can slow the progression of AD, but only if AD is diagnosed at early stages. We have previously introduced an ensemble of classifiers based approach for combining event related potentials obtained from different electrode locations as an effective approach for early diagnosis of AD. We further expand this approach and analyze its robustness and stability in two ways: comparing the diagnostic accuracy on hand selected and cleaned data vs. standard automated preprocessing, but more importantly, comparing the diagnostic accuracy on two different cohorts, whose data are collected under different settings: a research university lab and a community clinic.

关键词： Enterprise resource planning Proteins Biomedical signal processing Hospitals Alzheimer's disease Electrodes Robust stability Medical diagnostic imaging Biomarkers Electroencephalography

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Data Preprocessing in SVM-Based Keywords Extraction from Scientific Documents

Data Preprocessing in SVM-Based Keywords Extraction from Sci...

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International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Chunguo Wu Maurizio Marchese Yufei Wang Mikalai Krapivin Chaoyong Wang Xitong Li Yanchun Liang College of Computer Science and Technology Jilin University Changchun China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Department of Information Engineering and Computer Science University of Trento Povo Italy Jilin University Changchun Jilin CN Department of Fundamental Sciences Jilin Teachers Institute of Engineering and Technology Changchun China

关键词： Data preprocessing Data mining computer science Data engineering Natural languages Equations Frequency Automatic control Chaos Educational institutions

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Ontology-supported indexing in P2P networks of digital libraries

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International Journal of Web engineering and Technology 2008年第1期4卷 44-69页

作者： Alexakos, Christos E. Paraskevopoulos, Konstantinos I. Votis, Konstantinos V. Likothanassis, Spiridon D. Pattern Recognition Laboratory Department of Computer Engineering and Informatics University of Patras GR 26500 Patras Hellas Greece Pattern Recognition Laboratory Department of Computer Engineering and Informatics University of Patras Industrial Systems Institute Department of Computer Engineering and Informatics University of Patras Pattern Recognition Laboratory Managing Committee Artificial Intelligence Research Center University of Patras

Distributed Digital Libraries (DLs) integration is significant for the enforcement of novel searching mechanisms in the internet. The great heterogeneity of systems storing and providing digital content requires the introduction of interoperability aspects in order to resolve integration problems in a flexible and dynamic way. Our approach introduces an innovative service-oriented P2P system, which initialises a distributed ontology schema, semantically describing and indexing the digital content stored in distributed DLs. The proposed architecture enforces the distributed semantic index by defining virtual clusters consisting of nodes (peers) with similar or related content in order to provide efficient searching and recommendation mechanisms. Furthermore, a use-case example is presented in order to demonstrate the functionalities of the proposed architecture in a P2P network with DLs containing cultural material. Copyright © 2008 Inderscience Enterprises Ltd.

关键词： Digital libraries

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