Structural Pattern Recognition With Graph Edit Distance
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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
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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.
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.
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
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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.
Graph Based Representations In Pattern Recognition
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Author : Pasquale Foggia
language : en
Publisher: Springer
Release Date : 2017-05-08
Graph Based Representations In Pattern Recognition written by Pasquale Foggia and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-08 with Computers categories.
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.
Graph Based Representations In Pattern Recognition
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Author : Francisco Escolano
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-31
Graph Based Representations In Pattern Recognition written by Francisco Escolano 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 2007-05-31 with Computers categories.
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. The 23 revised full papers and 14 revised poster papers presented were carefully reviewed and selected from 54 submissions. The papers are organized in topical sections on 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.
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.
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.
Graph Based Representations In Pattern Recognition
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Author : Cheng-Lin Liu
language : en
Publisher: Springer
Release Date : 2015-05-04
Graph Based Representations In Pattern Recognition written by Cheng-Lin Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-04 with Computers categories.
This book constitutes the refereed proceedings of the 10th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2015, held in Beijing, China, in May 2015. The 36 papers presented in this volume were carefully reviewed and selected from 53 submissions. The accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation, 15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications.