Structural Pattern Recognition With Graph Edit Distance

Author : Kaspar Riesen
Publisher : Unknown
Page : 128 pages
File Size : 53,7 Mb
Release : 2015
Category : Electronic
ISBN : 3319272535

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Structural Pattern Recognition with Graph Edit Distance by Kaspar Riesen Pdf

This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED), one of the most flexible graph distance models available. The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: Formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm Describes a reformulation of GED to a quadratic assignment problem Illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem Reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework Examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time Includes appendices listing the datasets employed for the experimental evaluations discussed in the book Researchers and graduate students interested in the field of structural pattern recognition will find this focused work to be an essential reference on the latest developments in GED. Dr. Kaspar Riesen is a university lecturer of computer science in the Institute for Information Systems at the University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland.

Author : Michel Neuhaus,Horst Bunke
Publisher : World Scientific
Page : 245 pages
File Size : 40,5 Mb
Release : 2007
Category : Computers
ISBN : 9789812708175

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Bridging the Gap Between Graph Edit Distance and Kernel Machines by Michel Neuhaus,Horst Bunke Pdf

In graph-based structural pattern recognition, the idea is to transform patterns into graphs and perform the analysis and recognition of patterns in the graph domain ? commonly referred to as graph matching. A large number of methods for graph matching have been proposed. Graph edit distance, for instance, defines the dissimilarity of two graphs by the amount of distortion that is needed to transform one graph into the other and is considered one of the most flexible methods for error-tolerant graph matching.This book focuses on graph kernel functions that are highly tolerant towards structural errors. The basic idea is to incorporate concepts from graph edit distance into kernel functions, thus combining the flexibility of edit distance-based graph matching with the power of kernel machines for pattern recognition. The authors introduce a collection of novel graph kernels related to edit distance, including diffusion kernels, convolution kernels, and random walk kernels. From an experimental evaluation of a semi-artificial line drawing data set and four real-world data sets consisting of pictures, microscopic images, fingerprints, and molecules, the authors demonstrate that some of the kernel functions in conjunction with support vector machines significantly outperform traditional edit distance-based nearest-neighbor classifiers, both in terms of classification accuracy and running time.

Author : Michel Neuhaus,Horst Bunke
Publisher : World Scientific
Page : 245 pages
File Size : 43,8 Mb
Release : 2007
Category : Computers
ISBN : 9789812770202

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Bridging the Gap Between Graph Edit Distance and Kernel Machines by Michel Neuhaus,Horst Bunke Pdf

In graph-based structural pattern recognition, the idea is to transform patterns into graphs and perform the analysis and recognition of patterns in the graph domain OCo commonly referred to as graph matching. A large number of methods for graph matching have been proposed. Graph edit distance, for instance, defines the dissimilarity of two graphs by the amount of distortion that is needed to transform one graph into the other and is considered one of the most flexible methods for error-tolerant graph matching.This book focuses on graph kernel functions that are highly tolerant towards structural errors. The basic idea is to incorporate concepts from graph edit distance into kernel functions, thus combining the flexibility of edit distance-based graph matching with the power of kernel machines for pattern recognition. The authors introduce a collection of novel graph kernels related to edit distance, including diffusion kernels, convolution kernels, and random walk kernels. From an experimental evaluation of a semi-artificial line drawing data set and four real-world data sets consisting of pictures, microscopic images, fingerprints, and molecules, the authors demonstrate that some of the kernel functions in conjunction with support vector machines significantly outperform traditional edit distance-based nearest-neighbor classifiers, both in terms of classification accuracy and running time."

Author : Kaspar Riesen
Publisher : Springer
Page : 158 pages
File Size : 44,7 Mb
Release : 2016-01-09
Category : Computers
ISBN : 9783319272528

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Structural Pattern Recognition with Graph Edit Distance by Kaspar Riesen Pdf

This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm; describes a reformulation of GED to a quadratic assignment problem; illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem; reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework; examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time; includes appendices listing the datasets employed for the experimental evaluations discussed in the book.

Author : Xiaoyi Jiang,Miquel Ferrer,Andrea Torsello
Publisher : Springer
Page : 345 pages
File Size : 43,6 Mb
Release : 2011-05-05
Category : Computers
ISBN : 9783642208447

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Graph-Based Representations in Pattern Recognition by Xiaoyi Jiang,Miquel Ferrer,Andrea Torsello Pdf

This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2011, held in Münster, Germany, in May 2011. The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications.

Author : Kaspar Riesen
Publisher : Springer
Page : 158 pages
File Size : 47,8 Mb
Release : 2018-03-30
Category : Computers
ISBN : 3319801015

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Structural Pattern Recognition with Graph Edit Distance by Kaspar Riesen Pdf

This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm; describes a reformulation of GED to a quadratic assignment problem; illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem; reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework; examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time; includes appendices listing the datasets employed for the experimental evaluations discussed in the book.

Author : Edwin Hancock,Mario Vento
Publisher : Springer Science & Business Media
Page : 280 pages
File Size : 55,7 Mb
Release : 2003-06-18
Category : Computers
ISBN : 9783540404521

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Graph Based Representations in Pattern Recognition by Edwin Hancock,Mario Vento Pdf

The refereed proceedings of the 4th IAPR International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2003, held in York, UK in June/July 2003. The 23 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on data structures and representation, segmentation, graph edit distance, graph matching, matrix methods, and graph clustering.

Author : Adam Krzyzak,Ching Y. Suen,Andrea Torsello,Nicola Nobile
Publisher : Springer Nature
Page : 336 pages
File Size : 40,8 Mb
Release : 2023-01-01
Category : Computers
ISBN : 9783031230288

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Structural, Syntactic, and Statistical Pattern Recognition by Adam Krzyzak,Ching Y. Suen,Andrea Torsello,Nicola Nobile Pdf

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2022, held in Montreal, QC, Canada, in August 2022. The 30 papers together with 2 invited talks presented in this volume were carefully reviewed and selected from 50 submissions. The workshops presents papers on topics such as deep learning, processing, computer vision, machine learning and pattern recognition and much more.

Author : Andrea Torsello,Luca Rossi,Marcello Pelillo,Battista Biggio,Antonio Robles-Kelly
Publisher : Springer Nature
Page : 384 pages
File Size : 52,6 Mb
Release : 2021-04-09
Category : Computers
ISBN : 9783030739737

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Structural, Syntactic, and Statistical Pattern Recognition by Andrea Torsello,Luca Rossi,Marcello Pelillo,Battista Biggio,Antonio Robles-Kelly Pdf

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2020, held in Padua, Italy, in January 2021. The 35 papers presented in this volume were carefully reviewed and selected from 81 submissions. The accepted papers cover the major topics of current interest in pattern recognition, including classification and clustering, deep learning, structural matching and graph-theoretic methods, and multimedia analysis and understanding.

Author : Dit-Yan Yeung
Publisher : Springer Science & Business Media
Page : 959 pages
File Size : 51,6 Mb
Release : 2006-08-03
Category : Computers
ISBN : 9783540372363

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Structural, Syntactic, and Statistical Pattern Recognition by Dit-Yan Yeung Pdf

This is the proceedings of the 11th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2006 and the 6th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2006, held in Hong Kong, August 2006 alongside the Conference on Pattern Recognition, ICPR 2006. 38 revised full papers and 61 revised poster papers are included, together with 4 invited papers covering image analysis, character recognition, bayesian networks, graph-based methods and more.

Author : Pasi Fränti,Gavin Brown,Marco Loog,Francisco Escolano,Marcello Pelillo
Publisher : Springer
Page : 493 pages
File Size : 44,5 Mb
Release : 2014-08-13
Category : Computers
ISBN : 9783662444153

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Structural, Syntactic, and Statistical Pattern Recognition by Pasi Fränti,Gavin Brown,Marco Loog,Francisco Escolano,Marcello Pelillo Pdf

This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2014; comprising the International Workshop on Structural and Syntactic Pattern Recognition, SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The total of 25 full papers and 22 poster papers included in this book were carefully reviewed and selected from 78 submissions. They are organized in topical sections named: graph kernels; clustering; graph edit distance; graph models and embedding; discriminant analysis; combining and selecting; joint session; metrics and dissimilarities; applications; partial supervision; and poster session.

Author : Pasquale Foggia,Cheng-Lin Liu,Mario Vento
Publisher : Springer
Page : 290 pages
File Size : 46,5 Mb
Release : 2017-05-08
Category : Computers
ISBN : 9783319589619

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Graph-Based Representations in Pattern Recognition by Pasquale Foggia,Cheng-Lin Liu,Mario Vento Pdf

This book constitutes the refereed proceedings of the 11th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2017, held in Anacapri, Italy, in May 2017. The 25 full papers and 2 abstracts of invited papers presented in this volume were carefully reviewed and selected from 31 submissions. The papers discuss research results and applications in the intersection of pattern recognition, image analysis, graph theory, and also the application of graphs to pattern recognition problems in other fields like computational topology, graphic recognition systems and bioinformatics.

Author : Donatello Conte,Jean-Yves Ramel,Pasquale Foggia
Publisher : Springer
Page : 257 pages
File Size : 45,6 Mb
Release : 2019-06-10
Category : Computers
ISBN : 9783030200817

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Graph-Based Representations in Pattern Recognition by Donatello Conte,Jean-Yves Ramel,Pasquale Foggia Pdf

This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2019, held in Tours, France, in June 2019. The 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. The papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.

Author : Chen Chi Hau
Publisher : World Scientific
Page : 404 pages
File Size : 49,6 Mb
Release : 2020-04-04
Category : Computers
ISBN : 9789811211089

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Handbook Of Pattern Recognition And Computer Vision (6th Edition) by Chen Chi Hau Pdf

Author : Francisco Escolano,Mario Vento
Publisher : Springer
Page : 416 pages
File Size : 46,8 Mb
Release : 2007-08-20
Category : Computers
ISBN : 9783540729037

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Graph-Based Representations in Pattern Recognition by Francisco Escolano,Mario Vento Pdf

This book constitutes the refereed proceedings of the 6th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007, held in Alicante, Spain in June 2007. It covers matching, distances and measures, graph-based segmentation and image processing, graph-based clustering, graph representations, pyramids, combinatorial maps and homologies, as well as graph clustering, embedding and learning.