Graph-Based Representations in Pattern Recognition [electronic resource] : 8th IAPR-TC-15 International Workshop, GbRPR 2011, Münster, Germany, May 18-20, 2011. Proceedings / edited by Xiaoyi Jiang, Miquel Ferrer, Andrea Torsello.
By: Jiang, Xiaoyi [editor.].
Contributor(s): Ferrer, Miquel [editor.] | Torsello, Andrea [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 6658Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XI, 345 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642208447.Subject(s): Computer science | Computational complexity | Artificial intelligence | Computer vision | Computer graphics | Optical pattern recognition | Computer Science | Pattern Recognition | Image Processing and Computer Vision | Computer Imaging, Vision, Pattern Recognition and Graphics | Computer Graphics | Discrete Mathematics in Computer Science | Artificial Intelligence (incl. Robotics)DDC classification: 006.4 Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2011, held in Münster, Germany, in May 2011. The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications.
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This book constitutes the refereed proceedings of the 8th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2011, held in Münster, Germany, in May 2011. The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications.
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