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Graph-Based Representations in Pattern Recognition

10th IAPR-TC-15 International Workshop, GbRPR 2015, Beijing, China, May 13-15, 2015. Proceedings

  • Conference proceedings
  • © 2015
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Overview

Editors:
  1. Cheng-Lin Liu

    1. Institute of Automation of CAS, Beijing, China

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  2. Bin Luo

    1. Anhui University, Anhui, China

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  3. Walter G. Kropatsch

    1. Vienna University of Technology, Beijing, China

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  4. Jian Cheng

    1. Institute of Automation, Beijing, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9069)

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 2015.

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Table of contents (36 papers)

  1. Front Matter

    Pages 1-12
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  2. Graph-Based Representation

    1. Front Matter

      Pages 1-1
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    2. Approximation of Graph Edit Distance in Quadratic Time

      • Kaspar Riesen, Miquel Ferrer, Andreas Fischer, Horst Bunke
      Pages 3-12
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    3. Data Graph Formulation as the Minimum-Weight Maximum-Entropy Problem

      • Samuel de Sousa, Walter G. Kropatsch
      Pages 13-22
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    4. An Entropic Edge Assortativity Measure

      • Cheng Ye, Richard C. Wilson, Edwin R. Hancock
      Pages 23-33
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    5. A Subpath Kernel for Learning Hierarchical Image Representations

      • Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre
      Pages 34-43
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    6. Coupled-Feature Hypergraph Representation for Feature Selection

      • Zhihong Zhang, Jianbing Xiahou, Lu Bai, Edwin R. Hancock
      Pages 44-53
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    7. Reeb Graphs Through Local Binary Patterns

      • Ines Janusch, Walter G. Kropatsch
      Pages 54-63
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    8. Incremental Embedding Within a Dissimilarity-Based Framework

      • Rachid Hafiane, Luc Brun, Salvatore Tabbone
      Pages 64-73
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  3. Graph Matching

    1. Front Matter

      Pages 75-75
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    2. A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching

      • Miquel Ferrer, Francesc Serratosa, Kaspar Riesen
      Pages 77-86
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    3. Consensus of Two Graph Correspondences Through a Generalisation of the Bipartite Graph Matching

      • Carlos Francisco Moreno-García, Francesc Serratosa, Xavier Cortés
      Pages 87-97
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    4. Revisiting Volgenant-Jonker for Approximating Graph Edit Distance

      • William Jones, Aziem Chawdhary, Andy King
      Pages 98-107
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    5. A Hypergraph Matching Framework for Refining Multi-source Feature Correspondences

      • He Zhang, Bin Du, Yanjiang Wang, Peng Ren
      Pages 108-117
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    6. Kite Recognition by Means of Graph Matching

      • Kamel Madi, Hamida Seba, Hamamache Kheddouci, Charles-Edmont Bichot, Olivier Barge, Christine Chataigner et al.
      Pages 118-127
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    7. GEM++: A Tool for Solving Substitution-Tolerant Subgraph Isomorphism

      • Julien Lerouge, Pierre Le Bodic, Pierre Héroux, Sébastien Adam
      Pages 128-137
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    8. A Graph Database Repository and Performance Evaluation Metrics for Graph Edit Distance

      • Zeina Abu-Aisheh, Romain Raveaux, Jean-Yves Ramel
      Pages 138-147
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    9. Improving Hausdorff Edit Distance Using Structural Node Context

      • Andreas Fischer, Seiichi Uchida, Volkmar Frinken, Kaspar Riesen, Horst Bunke
      Pages 148-157
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    10. Learning Graph Model for Different Dimensions Image Matching

      • Haoyi Zhou, Xiao Bai, Jun Zhou, Haichuan Yang, Yun Liu
      Pages 158-167
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    11. VF2 Plus: An Improved version of VF2 for Biological Graphs

      • Vincenzo Carletti, Pasquale Foggia, Mario Vento
      Pages 168-177
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  1. Graph-Based Representations in Pattern Recognition

Keywords

About this book

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.

Editors and Affiliations

  • Institute of Automation of CAS, Beijing, China

    Cheng-Lin Liu

  • Anhui University, Anhui, China

    Bin Luo

  • Vienna University of Technology, Beijing, China

    Walter G. Kropatsch

  • Institute of Automation, Beijing, China

    Jian Cheng

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