Structural Pattern Recognition with Graph Edit Distance by Kaspar Riesen - ISBN: 9783319801018
Paperback
This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem;

Structural Pattern Recognition with Graph Edit Distance

Approximation Algorithms and Applications

$152.10

  • Paperback

    158 pages

  • Release Date

    30 March 2018

Check Delivery Options

Summary

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 q…

Book Details

ISBN-13:9783319801018
ISBN-10:3319801015
Author:Kaspar Riesen
Publisher:Springer International Publishing AG
Imprint:Springer International Publishing AG
Format:Paperback
Number of Pages:158
Release Date:30 March 2018
Weight:454g
Dimensions:235mm x 155mm
Series:Advances in Computer Vision and Pattern Recognition
What They're Saying

Critics Review

“The book presents the use of graphs in the field of structural pattern recognition. … The book is written in a very accessible fashion. The author gives many examples presenting the notations and problems considered. The book is suitable for graduate students and is an ideal reference for researchers and professionals interested in graph edit distance and its applications in pattern recognition.” (Krzystof Gdawiec, zbMATH 1365.68004, 2017)

“This book is exactly about this fascinating topic: the definition, the study of properties, and the areas of application of the graph edit distance in the realm of structural pattern recognition. … The book’s intended audience is advanced graduate students in science and engineering, but also professionals working in relevant fields.” (Dimitrios Katsaros, Computing Reviews, computingreviews.com, August, 2016)

About The Author

Kaspar Riesen

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.

Returns

This item is eligible for free returns within 30 days of delivery. See our returns policy for further details.