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Graph-Based Representations in Pattern Recognition : 12th IAPR-TC-15 International Workshop, GbRPR 2019, Tours, France, June 19-21, 2019, Proceedings / edited by Donatello Conte, Jean-Yves Ramel, Pasquale Foggia.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11510
- Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11510
- Language:
- English
- Subjects (All):
- Pattern recognition systems.
- Computer science-Mathematics.
- Discrete mathematics.
- Computer graphics.
- Algorithms.
- Artificial intelligence-Data processing.
- Artificial intelligence.
- Automated Pattern Recognition.
- Discrete Mathematics in Computer Science.
- Computer Graphics.
- Data Science.
- Artificial Intelligence.
- Local Subjects:
- Automated Pattern Recognition.
- Discrete Mathematics in Computer Science.
- Computer Graphics.
- Algorithms.
- Data Science.
- Artificial Intelligence.
- Physical Description:
- 1 online resource (X, 247 pages) : 92 illustrations, 74 illustrations in color.
- Edition:
- 1st ed. 2019.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2019.
- System Details:
- text file PDF
- Summary:
- This book constitutes the refereed proceedings of the 12th IAPR-TC-15 International Workshop on Graph-Based Representation in Pattern Recognition, GbRPR 2019, held in Tours, France, in June 2019. The 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. The papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. They cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems. .
- Other Format:
- Printed edition:
- ISBN:
- 978-3-030-20081-7
- 9783030200817
- Access Restriction:
- Restricted for use by site license.
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