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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

4th IAPR International Workshop on Graph Based Representatio...

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

ISBN: (纸本)354040452X

the proceedings contain 23 papers. the special focus in this conference is on Data Structures and Representation. the topics include: Construction of combinatorial pyramids;on graphs with unique node labels;maximal independent directed edge set;functional modeling of structured images;building of symbolic hierarchical graphs for feature extraction;comparison and convergence of two topological models for 3D image segmentation;tree edit distance from information theory;self-organizing graph edit distance;graph edit distance with node splitting and merging, and its application to diatom identification;orthonormal kernel kronecker product graph matching;theoretical analysis and experimental comparison of graph matching algorithms for database filtering;a comparison of three maximum common subgraph algorithms on a large database of labeled graphs;swap strategies for graph matching;graph matching using spectral seriation and string edit distance;graph polynomials, principal pivoting, and maximum independent sets;graph partition for matching;spectral clustering of graphs;comparison of distance measures for graph-based clustering of documents;some experiments on clustering a set of strings;a new median graph algorithm;graph clustering using the weighted minimum common supergraph;ACM attributed graph clustering for learning classes of images and a competitive winner-takes-all architecture for classification and pattern recognition of structures.

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A competitivewinner-takes-all architecture for classification and pattern recognition of structures

A competitivewinner-takes-all architecture for classificatio...

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： Jain, Brijnesh J. Wysotzki, Fritz Dept. of Electrical Engineering and Computer Science Technical University Berlin Germany

ISBN: (纸本)354040452X

We propose a winner-takes-all (WTA) classifier for structures represented by graphs. WTA classification follows the principle elimination of competition. the input structure is assigned to the class corresponding to the winner of the competition. In experiments we investigate the performance of the WTA classifier and compare it with the canonical maximum similarity (MS) classifier. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern recognition

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Learning from Diffusion-Weighted Magnetic Resonance Images Using graph Kernels 11th

Learning from Diffusion-Weighted Magnetic Resonance Images U...

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11th iapr-TC15 international workshop on graph-based representations in pattern recognition (gbrpr)

作者： Takerkart, Sylvain Berton, Gottfried Malfait, Nicole Dupe, Francois-Xavier Aix Marseille Univ CNRS INT Marseille France Aix Marseille Univ CNRS Cent Marseille LIF Marseille France

ISBN: (纸本)9783319589619;9783319589602

Diffusion-weighted magnetic resonance imaging (DWI) is a scanning procedure that allows infering the anatomical connectivity of the brain non invasively. DWI can be used to segment the brain into a set of relevant sub-regions, yielding what is called a parcellation in the neuroimaging literature. In this paper, we introduce a generic framework that allows building predictive models using parcellations obtained on a single individual. It consists in constructing attributed region adjacency graphs to represent the parcellations and using suitable graph kernels to exploit the versatility of kernel methods. We demonstrate the relevance of this framework on real data, by showing that we can predict the age range of an individual from the connectivity structure of its corpus callosum, the main hub of connections between the left and right hemispheres of the brain. Furthermore, we study the behavior of different graph kernels for this task. this work opens new opportunities to identify DWI-based biomarkers of neurodegenerative and psychiatric diseases.

关键词： Region-adjacency graphs graph kernel Magnetic resonance imaging Brain connectivity Brain parcellation

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graph-based representations in pattern recognition 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Mario Vento Pasquale Foggia Vincenzo Carletti Donatello Conte

ISBN: (数字)9783031427954

ISBN: (纸本)9783031427947

this book constitutes the refereed proceedings of the 13th iapr-TC-15 international workshop on graph-based representations in pattern recognition, gbrpr 2023, which took place in Vietri sul Mare, Italy, in September 2023.;the 16 full papers included in this book were carefully reviewed and selected from 18 submissions. they were organized in topical sections on graph kernels and graph algorithms; graph neural networks; and graph-based representations and applications.

关键词： pattern recognition Discrete Mathematics in Computer Science Computer graphics Algorithms Data Structures and Information theory Artificial Intelligence

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graph partition for matching

Graph partition for matching

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： Qiu, Huaijun Hancock, Edwin R. Department of Computer Science University of York Heslington YorkYO10 5DD United Kingdom

ISBN: (纸本)354040452X

Although inexact graph-matching is a problem of potentially exponential complexity, the problem may be simplified by decomposing the graphs to be matched into smaller subgraphs. If this is done, then the process may cast into a hierarchical framework or cast in a way which is amenable to parallel computation. In this paper we demonstrate how the Fiedler-vector can be used to partition graphs for the purposes of decomposition. We show how the resulting subgraphs can be matched using a variety of algorithms. We demonstrate the utility of the resulting graph-matching method on both real work and synthetic data. Here it proves to provide results which are comparable with a number of stateof- the-art graph matching algorithms. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern matching

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Orthonormal kernel kronecker product graph matching

Orthonormal kernel kronecker product graph matching

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： van Wyk, Barend Jacobus van Wyk, Michaël Antonie Kentron a Division of Denel Centurion South Africa Rand Afrikaans University Johannesburg South Africa

ISBN: (纸本)354040452X

this paper introduces a novel algorithm for performing Attributed graph Matching (AGM). the Orthonormal Kernel Kronecker Product graph Matching (OKKPGM) algorithm is based on the recently introduced Kronecker Product graph Matching (KPGM) formulation. However, unlike previous algorithms based on the KPGM formulation which avoided explicit compatibility calculations, the OKKPGM algorithm obtains an estimate to the Kronecker Match Matrix (KMM) using kernel function evaluations. A permutation sub-matrix (match matrix), is then inferred from the KMM using a summation procedure. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Artificial intelligence

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graph matching using spectral seriation and string edit distance

Graph matching using spectral seriation and string edit dist...

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： Robles-Kelly, Antonio Hancock, Edwin R. Department of Computer Science University of York YorkY01 5DD United Kingdom

ISBN: (纸本)354040452X

this paper is concerned with computing graph edit distance. One of the criticisms that can be leveled at existing methods for computing graph edit distance is that it lacks the formality and rigour of the computation of string edit distance. Hence, our aim is to convert graphs to string sequences so that string matching techniques can be used. To do this we use graph spectral seriation method to convert the adjacency matrix into a string or sequence order. We show how the serial ordering can be established using the leading eigenvector of the graph adjacency matrix. We pose the problem of graph-matching as maximum a posteriori probability alignment of the seriation sequences for pairs of graphs. this treatment leads to an expression in which for edit cost is the negative logarithm of the a posteriori sequence alignment probability. To compute the string alignment probability we provide models of the edge compatibility error and the probability of individual node correspondences. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern matching

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graph clustering using the weighted minimum common supergraph

Graph clustering using the weighted minimum common supergrap...

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： Bunke, Horst Foggia, P. Guidobaldi, C. Vento, M. Institut für Informatik und angwandte Mathematik Universität Bern Neubrückstrasse 10 BernCH-3012 Switzerland Dipartimento di Informatica e Sistemistica Università di Napoli "Federico II" Via Claudio 21 NapoliI-80125 Italy Dipartimento di Ingegneria dell’Informazione ed Ingegneria Elettrica Università di Salerno via P.te Don Melillo FiscianoSAI-84084 Italy

ISBN: (纸本)354040452X

graphs are a powerful and versatile tool useful for representing patterns in various subfields of science and engineering. In many applications, for example, in pattern recognition and computer vision, it is required to measure the similarity of objects for clustering similar patterns. In this paper a new structural method, the Weighted Minimum Common Supergraph (WMCS), for representing a cluster of patterns is proposed. Using this method it becomes easy to extract the common information shared in the patterns of a cluster and separate this information from noise and distortions that usually affect graphs representing real objects. Moreover, experimental results show that WMCS is suitable for performing graph clustering. © Springer-Verlag Berlin Heidelberg 2003.

关键词： pattern recognition

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ACM attributed graph clustering for learning classes of images

ACM attributed graph clustering for learning classes of imag...

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： Miguel Angel Lozano Francisco Escolano

ISBN: (纸本)354040452X

In a previous work we have adapted the Asymmetric Clustering Model (ACM) to the domain of non-attributed graphs. We use our Comb algorithm for graph matching, a population-based method which performs multi-point explorations of the discrete space of feasible solutions. Given this algorithm we define an incremental method to obtain a prototypical graph by fusing the elements of the ensemble weighted by their prior probabilities of belonging to the class. graph-matching and incremental fusion are integrated in a EM clustering algorithm. In this paper, we adapt the latter ACM clustering model to deal with attributed graphs, where these attributes are probability density functions associated to nodes and edges. In order to do so, we modify the incremental method for obtaining a prototypical graph to update these pdf’s provided that they are statistically compatible with those of the corresponding nodes and edges. this graph-clustering approach is successfully tested in the domain of Mondrian images (images built on rectangular patches of colored textures) because our final purpose is to the unsupervised learning of image classes. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Clustering algorithms

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Construction of combinatorial pyramids

Construction of combinatorial pyramids

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4th iapr international workshop on graph based representations in pattern recognition, gbrpr 2003

作者： Brun, Luc Kropatsch, Walter G. Université de Reims France Institute for Computer-aided Automation Pattern Recognition and Image Processing Group Vienna Univ. of Technology Austria

ISBN: (纸本)354040452X

Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Each vertex of a reduced graph corresponds to a connected set of vertices in the level below. One connected set of vertices reduced into a single vertex at the above level is called the reduction window of this vertex. In the same way, a connected set of vertices in the base level graph reduced to a single vertex at a given level is called the receptive field of this vertex. the graphs used in the pyramid may be region adjacency graphs, dual graphs or combinatorial maps. this last type of pyramids are called Combinatorial Pyramids. Compared to usual graph data structures, combinatorial maps encode one graph and its dual within a same formalism and offer an explicit encoding of the orientation of edges around vertices. this paper describes the construction scheme of a Combinatorial Pyramid. We also provide a constructive definition of the notions of reduction windows and receptive fields within the Combinatorial Pyramid framework. © Springer-Verlag Berlin Heidelberg 2003.

关键词： graphic methods

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