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检索条件"任意字段=7th International Workshop on Graph-Based Representations in Pattern Recognition"

共 189 条记录，以下是121-130 订阅

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A fast construction of the distance graph used for the classification of heterogeneous electron microscopic projections

A fast construction of the distance graph used for the class...

引用

6th international workshop on graph-based representations in pattern recognition

作者： Kalinowski, Miroslaw Daurat, Alain Herman, Gabor T. CUNY Grad Ctr Dept Comp Sci 365 5th Ave New York NY 10016 USA Univ Louis Pasteur Strasbourg 1 LSIIT CNRS UMR 7005Pole API F-67400 Illkirch Graffenstaden France

ISBN: (纸本)9783540729020

It has been demonstrated that the difficult problem of classifying heterogeneous projection images, similar to those found in 3D electron microscopy (3D-EM) of macromolecules, can be successfully solved by finding an approximate Max k-Cut of an appropriately constructed weighted graph. Despite of the large size (thousands of nodes) of the graph and the theoretical computational complexity of finding even an approximate Max k-Cut, an algorithm has been proposed that finds a good (from the classification perspective) approximate solution within several minutes (running on a standard PC). However, the task of constructing the complete weighted graph (that represents an instance of the projection image classification problems) is computationally expensive. Due to the large number of edges, the computation of edge weights can take tens of hours for graphs containing several thousand nodes. We propose a method, which utilizes an early termination technique, to significantly reduce the computational cost of constructing such graphs. We compare, on synthetic data sets that resemble projection sets encountered in 3D-EM, the performance of our method with that of a brute-force approach and a method based on nearest neighbor search.

关键词： graph theory

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Hierarchy construction schemes within the scale set framework

Hierarchy construction schemes within the scale set framewor...

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6th international workshop on graph-based representations in pattern recognition

作者： Pruvot, Jean-Hugues Brun, Luc CNRS UMR 6072 Image Team GREYC Lab 6 Blvd Marechal Juin F-14050 Caen France

ISBN: (纸本)9783540729020

Segmentation algorithms based on an energy minimisation framework often depend on a scale parameter which balances a fit to data and a regularising term. Irregular pyramids are defined as a stack of graphs successively reduced. Within this framework, the scale is often defined implicitly as the height in the pyramid. However, each level of an irregular pyramid can not usually be readily associated to the global optimum of an energy or a global criterion on the base level graph. this last drawback is addressed by the scale set framework designed by Guigues. the methods designed by this author allow to build a hierarchy and to design cuts within this hierarchy which globally minimise an energy. this paper studies the influence of the construction scheme of the initial hierarchy on the resulting optimal cuts. We propose one sequential and one parallel method with two variations within both. Our sequential methods provide partitions near an energy lower bound defined in this paper. Parallel methods require less execution times than the sequential method of Guigues even on sequential machines.

关键词： pattern recognition

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Proceedings of the 7th international workshop on pattern recognition in Information Systems PRIS 2007;in Conjunction with ICEIS 2007

Proceedings of the 7th International Workshop on Pattern Rec...

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7th international workshop on pattern recognition in Information Systems PRIS 2007;In Conjunction with ICEIS 2007

ISBN: (纸本)9789728865931

the proceedings contain 24 papers. the topics discussed include: complex statistical models for object recognition and mass spectrometry;semi-supervised and active learning;reliable biometrical analysis in biodiversity information systems;string patterns: from single clustering to ensemble methods and validation;a novel distance measure for interval data;bridging the gap between Naive Bayes and maximum entropy text classification;a weight vector feature for 3D shape matching;extending morphological signatures for visual pattern recognition;a contribution to ancient cadastral maps interpretation through colour analysis;texture learning by fractal compression;incremental non-negative matrix factorization for dynamic background modelling;and improving isometric hand gesture identification for HCI based on independent component analysis in bio-signal processing.

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Extending morphological signatures for visual pattern recognition

Extending morphological signatures for visual pattern recogn...

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7th international workshop on pattern recognition in Information Systems PRIS 2007;In Conjunction with ICEIS 2007

作者： Lefèvre, Sébastien LSIIT CNRS University Louis Pasteur Strasbourg i Parc d'Innovation Bvd Brant 67412 Illkirch Cedex France

ISBN: (纸本)9789728865931

Morphological signatures are powerful descriptions of the image content which are based on the framework of mathematical morphology. these signatures can be computed on a global or local scale: they are called pattern spectra (or granulometries and antigranulometries) when measured on the complete images and morphological profiles when related to single pixels. their goal is to measure shape distribution instead of intensity distribution, thus they can be considered as a relevant alternative to classical intensity histograms, in the context of visual pattern recognition. A morphological signature (either a pattern spectrum or a morphological profile) is defined as a series of morphological operations (namely openings and closings) considering a predefined pattern called structuring element. Even if it can be used directly to solve various pattern recognition problems related to image data, the simple definitions given in the binary and grayscale cases limit its usefulness in many applications. In this paper, we introduce several 2-D extensions to the classical 1-D morphological signature. More precisely, we elaborate morphological signatures which try to gather more image information and do not only include a dimension related to the object size, but also consider on a second dimension a complementary information relative to size, intensity or spectral information. Each of the 2-D morphological signature proposed in this paper can be defined either on a global or local scale and for a particular kind of images among the most commonly ones (binary, grayscale or multispectral images). We also illustrate these signatures by several real-life applications related to object recognition and remote sensing.

关键词： Mathematical morphology

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Incremental non-negative matrix factorization for dynamic background modelling

Incremental non-negative matrix factorization for dynamic ba...

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7th international workshop on pattern recognition in Information Systems PRIS 2007;In Conjunction with ICEIS 2007

作者： Bucak, Serhat S. Gunsel, Bilge Gursoy, Ozan Multimedia Signal Processing and Pattern Recognition Lab. Dept. of Electronics and Comm. Eng. Istanbul Technical University 34469 Maslak Istanbul Turkey

ISBN: (纸本)9789728865931

In this paper, an incremental algorithm which is derived from Non-negative Matrix Factorization (NMF) is proposed for background modeling in surveillance type of video sequences. the adopted algorithm, which is called as Incremental NMF (INMF), is capable of modeling dynamic content of the surveillance video and controlling contribution of the subsequent observations to the existing representation properly. INMF preserves additive, parts-based representation, and dimension reduction capability of NMF without increasing the computational load. Test results are reported to compare background modeling performances of batch-mode and incremental NMF in surveillance type of video. Moreover, test results obtained by the incremental PCA are also given for comparison purposes. It is shown that INMF outperforms the conventional batch-mode NMF in all aspects of dynamic background modeling. Although object tracking performance of INMF and the incremental PCA are comparable, INMF is much more robust to illumination changes.

关键词： Non-negative matrix factorization

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Combining pattern recognition modalities at the sensor level via kernel fusion

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7th international workshop on Multiple Classifier Systems

作者： Mottl, Vadim Tatarchuk, Alexander Sulimova, Valentina Krasotkina, Olga Seredin, Oleg Russian Acad Sci Ctr Comp Moscow 117968 Russia Tula State Univ Tula Russia

ISBN: (纸本)9783540724810

the problem of multi-modal pattern recognition is considered under the assumption that the kemel-based approach is applicable within each particular modality. the Cartesian product of the linear spaces into which the respective kernels embed the output scales of single sensor is employed as an appropriate joint scale corresponding to the idea of combining modalities, actually, at the sensor level. From this point of view, the known kernel fusion techniques, including Relevance and Support Kernel Machines, offer a toolkit of combining pattern recognition modalities. We propose an SVM-based quasi-statistical approach to multi-modal pattern recognition which covers both of these modes of kernel fusion.

关键词： kernel-based pattern recognition support vector machines combining modalities kernel fusion

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Algorithms in Bioinformatics - 7th international workshop, WABI 2007, Proceedings

Algorithms in Bioinformatics - 7th International Workshop, W...

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7th international workshop on Algorithms in Bioinformatics, WABI 2007

ISBN: (纸本)9783540741251

the proceedings contain 38 papers. the topics discussed include: shotgun protein sequencing;locality kernels for protein classification;when less is more: improving classification of protein families with a minimal set of global features;fault tolerance for large scale protein 3D reconstruction from contact maps;bringing folding pathways into strand pairing prediction;genotype error detection using hidden Markov models of haplotype diversity;haplotype inference via hierarchical genotype parsing;seeded tree alignment and planar tanglegram layout;a graph clustering approach to weak motif recognition;informative motifs in protein family alignments;topology independent protein structural alignment;generalized pattern search and mesh adaptive direct search algorithms for protein structure prediction;defining and computing optimum RMSD for gapped multiple structure alignment;and using protein domains to improve the accuracy of ab initio gene finding.

关键词： Bioinformatics

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Multiple Classifier Systems - 7th international workshop, MCS 2007, Proceedings

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7th international workshop on Multiple Classifier Systems, MCS 2007

ISBN: (纸本)9783540724810

the proceedings contain 51 papers. the topics discussed include: combining pattern recognition modalities at the sensor level via kernel fusion;deriving the kernel from training data;classifiers fusion in recognition of wheat varieties;an improved random subspace method and its application to EEG signal classification;confidence based gating of colour features for face authentication;serial fusion of fingerprint and face matchers;information theoretic combination of classifiers with application to AdaBoost;interactive boosting for image classification;selecting diversifying heuristics for cluster ensembles;classifier ensembles for vector space embedding of graphs;cascading for nominal data;feature subspace ensembles: a parallel classifier combination scheme using feature selection;optimal classifier combination rules for verification and identification systems;an experimental study on rotation forest ensembles;and biometric person authentication is a multiple classifier problem.

关键词： Multi agent systems

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Model-based testing of service infrastructure components

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19th IFIP international Conference on Testing of Communicating Systems/7th international workshop on Formal Approaches to Testing of Software (TESTCOM/FATES 2007)

作者： Goenczy, Laszlo Heckel, Reiko Varro, Daniel Budapest Univ Technol & Econ Dept Measurement & Informat Syst Magyar Tudosok Krt 2 H-1117 Budapest Hungary Univ Leicester Dept Comp Sci Leicester LE1 7RH Leics England

ISBN: (纸本)9783540730651

We present a methodology for testing service infrastructure components described in a high-level (UML-like) language. the technique of graph transformation is used to precisely capture the dynamic aspect of the protocols which is the basis of state space generation. then we use model checking techniques to find adequate test sequences for a given requirement. To illustrate our approach, we present the case study of a fault tolerant service broker which implements a well-known dependability pattern at the level of services. Finally, a compact Petri Net representation is derived by workflow mining techniques to generate faithful test cases in a non-deterministic, distributed environment. Note that our methodology is applicable at the architectural level rather than for testing individual service instances only.

关键词： model-based testing graph transformation model checking fault-tolerant services

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the neutral point method for kernel-based combination of disjoint training data in multi-modal pattern recognition

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7th international workshop on Multiple Classifier Systems

作者： Windridge, David Mottl, Vadim Tatarchuk, Alexander Eliseyev, Andrey Univ Surrey Ctr Vis Speech & Signal Proc Guildford GU2 7XH Surrey England Russian Acad Sci Ctr Comp Moscow 119991 Russia Moscow Phys Tech Inst Inst Per 9 Dolgoprudnyi 141700 Russia

ISBN: (纸本)9783540724810

Multiple modalities present potential difficulties for kernel-based pattern recognition in consequence of the lack of inter-modal kernel measures. this is particularly apparent when training sets for the differing modalities are disjoint. thus, while it is always possible to consider the problem at the classifier fusion level, it is conceptually preferable to approach the matter from a kernel-based perspective. By interpreting the aggregate of disjoint training sets as an entire data set with missing inter-modality measurements to be filled in by appropriately chosen substitutes, we arrive at a novel kemel-based technique, the neutral-point method. On further theoretical analysis, it transpires that the method is, in structural terms, a kernel-based analog of the well-known sum rule combination scheme. We therefore expect the method to exhibit similar error-canceling behavior, and thus constitute a robust and conservative strategy for the treatment of kemel-based multi-modal data.

关键词： kernel-based pattern recognition combining modalities kernel fusion classifier fusion

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