Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10310)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
Conference proceedings info: GbRPR 2017.
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (25 papers)
-
Image and Shape Analysis
-
Large Graphs and Social Networks
Other volumes
-
Graph-Based Representations in Pattern Recognition
Keywords
- complex networks
- dynamic networks
- graph algorithms
- graph matching
- optimization
- bipartite graph matching
- clustering
- financial markets
- graph classification
- graph clustering
- graph edit distance
- graph kernels
- graph-based imagaeand shape analysis
- graph-based representations
- large graphs and social network analysis
- magnetic resonance imaging
- robustness
- saliency detection
- structural pattern recognition
- data structures
- algorithm analysis and problem complexity
About this book
Editors and Affiliations
Bibliographic Information
Book Title: Graph-Based Representations in Pattern Recognition
Book Subtitle: 11th IAPR-TC-15 International Workshop, GbRPR 2017, Anacapri, Italy, May 16–18, 2017, Proceedings
Editors: Pasquale Foggia, Cheng-Lin Liu, Mario Vento
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-58961-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-58960-2Published: 10 May 2017
eBook ISBN: 978-3-319-58961-9Published: 08 May 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XV, 289
Number of Illustrations: 40 b/w illustrations, 60 illustrations in colour
Topics: Pattern Recognition, Image Processing and Computer Vision, Computer Graphics, Discrete Mathematics in Computer Science, Data Structures, Algorithm Analysis and Problem Complexity