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Structural Pattern Recognition With Graph Edit Distance


Structural Pattern Recognition With Graph Edit Distance
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Bridging The Gap Between Graph Edit Distance And Kernel Machines


Bridging The Gap Between Graph Edit Distance And Kernel Machines
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Author : Michel Neuhaus
language : en
Publisher: World Scientific
Release Date : 2007

Bridging The Gap Between Graph Edit Distance And Kernel Machines written by Michel Neuhaus and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.


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.



Structural Pattern Recognition With Graph Edit Distance


Structural Pattern Recognition With Graph Edit Distance
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Author : Kaspar Riesen
language : en
Publisher:
Release Date : 2015

Structural Pattern Recognition With Graph Edit Distance written by Kaspar Riesen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.


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.



Structural Pattern Recognition With Graph Edit Distance


Structural Pattern Recognition With Graph Edit Distance
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Author : Kaspar Riesen
language : en
Publisher: Springer
Release Date : 2016-01-09

Structural Pattern Recognition With Graph Edit Distance written by Kaspar Riesen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-09 with Computers categories.


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.



Syntactic And Structural Pattern Recognition


Syntactic And Structural Pattern Recognition
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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 1990

Syntactic And Structural Pattern Recognition written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.


This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.



Structural Syntactic And Statistical Pattern Recognition


Structural Syntactic And Statistical Pattern Recognition
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Author : Xiao Bai
language : en
Publisher: Springer
Release Date : 2018-08-10

Structural Syntactic And Statistical Pattern Recognition written by Xiao Bai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-10 with Computers categories.


This book constitutes the proceedings of the Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2018, held in Beijing, China, in August 2018. The 49 papers presented in this volume were carefully reviewed and selected from 75 submissions. They were organized in topical sections named: classification and clustering; deep learning and neurla networks; dissimilarity representations and Gaussian processes; semi and fully supervised learning methods; spatio-temporal pattern recognition and shape analysis; structural matching; multimedia analysis and understanding; and graph-theoretic methods.



Structural Syntactic And Statistical Pattern Recognition


Structural Syntactic And Statistical Pattern Recognition
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Author : Dit-Yan Yeung
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-08-03

Structural Syntactic And Statistical Pattern Recognition written by Dit-Yan Yeung and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-03 with Computers categories.


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.



Structural Syntactic And Statistical Pattern Recognition


Structural Syntactic And Statistical Pattern Recognition
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Author : Pasi Fränti
language : en
Publisher: Springer
Release Date : 2014-08-13

Structural Syntactic And Statistical Pattern Recognition written by Pasi Fränti and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-13 with Computers categories.


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.



Pattern Recognition And String Matching


Pattern Recognition And String Matching
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Author : Dechang Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-11-30

Pattern Recognition And String Matching written by Dechang Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-11-30 with Mathematics categories.


The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes students and professionals in computer science, mathematics, statistics, and electrical engineering. We wish to thank all the authors for their valuable efforts, which made this book a reality. Thanks also go to all reviewers who gave generously of their time and expertise.



Structural Syntactic And Statistical Pattern Recognition


Structural Syntactic And Statistical Pattern Recognition
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Author : Antonio Robles-Kelly
language : en
Publisher: Springer
Release Date : 2016-11-04

Structural Syntactic And Statistical Pattern Recognition written by Antonio Robles-Kelly and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Computers categories.


This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR. The 51 full papers presented were carefully reviewed and selected from 68 submissions. They are organized in the following topical sections: dimensionality reduction, manifold learning and embedding methods; dissimilarity representations; graph-theoretic methods; model selection, classification and clustering; semi and fully supervised learning methods; shape analysis; spatio-temporal pattern recognition; structural matching; text and document analysis.



Structural Syntactic And Statistical Pattern Recognition


Structural Syntactic And Statistical Pattern Recognition
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Author : Andrea Torsello
language : en
Publisher: Springer Nature
Release Date : 2025-01-30

Structural Syntactic And Statistical Pattern Recognition written by Andrea Torsello and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-30 with Computers categories.


This book constitutes the proceedings of the Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2024, which took place in Venice, Italy, during September 9-11, 2024. The 19 full papers presented in this volume were carefully reviewed and selected from 27 submissions. The proceedings focus on pattern recognition, including classification and clustering, deep learning, structural matching and graph-theoretic methods, and multimedia analysis and understanding.