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ISBN: 9783540252702

Many vision problems have to deal with di?erent entities (regions, lines, line junctions, etc.) and their relationships. These entities together with their re- tionships may be encoded us… Plus…

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Graph-Based Representations in Pattern Recognition 5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings - Vento, Mario (Herausgeber); Brun, Luc (Herausgeber)
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Graph-Based Representations in Pattern Recognition 5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings - nouveau livre

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Graph-Based Representations in Pattern Recognition 5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings - Vento, Mario (Herausgeber); Brun, Luc (Herausgeber)
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Graph-Based Representations in Pattern Recognition 5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings - nouveau livre

2005

ISBN: 3540252703

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Graph-Based Representations in Pattern Recognition - Luc Brun; Mario Vento
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Graph-Based Representations in Pattern Recognition - Livres de poche

2005, ISBN: 9783540252702

5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings, Buch, Softcover, [PU: Springer Berlin], Springer Berlin, 2005

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Graph-Based Representations in Pattern Recognition

This book constitutes the refereed proceedings of the 5th IAPR International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2005, held in Poitiers, France in April 2005.The 18 revised full papers and 17 revised poster papers presented were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections on graph representations, graphs and linear representations, combinatorial maps, matching, hierarchical graph abstraction and matching, inexact

Informations détaillées sur le livre - Graph-Based Representations in Pattern Recognition


EAN (ISBN-13): 9783540252702
ISBN (ISBN-10): 3540252703
Livre de poche
Date de parution: 2005
Editeur: Springer Berlin
404 Pages
Poids: 0,608 kg
Langue: eng/Englisch

Livre dans la base de données depuis 2007-05-29T14:33:40+02:00 (Paris)
Page de détail modifiée en dernier sur 2023-11-16T21:08:21+01:00 (Paris)
ISBN/EAN: 9783540252702

ISBN - Autres types d'écriture:
3-540-25270-3, 978-3-540-25270-2
Autres types d'écriture et termes associés:
Auteur du livre: brun, bru, geometry, brün
Titre du livre: graph based representations pattern recognition, base france, représentation, international graphics, april, proceedings international workshop, computer


Données de l'éditeur

Auteur: Luc Brun; Mario Vento
Titre: Lecture Notes in Computer Science; Image Processing, Computer Vision, Pattern Recognition, and Graphics; Graph-Based Representations in Pattern Recognition - 5th IAPR International Workshop, GbRPR 2005, Poitiers, France, April 11-13, 2005, Proceedings
Editeur: Springer; Springer Berlin
384 Pages
Date de parution: 2005-03-23
Berlin; Heidelberg; DE
Poids: 1,250 kg
Langue: Anglais
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
POD
XII, 384 p.

BC; Pattern Recognition; Hardcover, Softcover / Informatik, EDV/Anwendungs-Software; Mustererkennung; Verstehen; Informatik; classification; computational graph theory; computer vision; database; filtering; fingerprint; graph matching; graph-based methods; graph-based representations; graph-theoretic methods; image analysis; object recognition; pattern recognition; programming; topology; data structures; Image Processing and Computer Vision; Computer Graphics; Discrete Mathematics in Computer Science; Data Structures; Automated Pattern Recognition; Computer Vision; Computer Graphics; Discrete Mathematics in Computer Science; Data Science; Maschinelles Sehen, Bildverstehen; Grafikprogrammierung; Mathematik für Informatiker; Diskrete Mathematik; Datenbanken; EA

Graph Representations.- Hypergraph-Based Image Representation.- Vectorized Image Segmentation via Trixel Agglomeration.- Graph Transformation in Document Image Analysis: Approaches and Challenges.- Graphical Knowledge Management in Graphics Recognition Systems.- A Vascular Network Growth Estimation Algorithm Using Random Graphs.- Graphs and Linear Representations.- A Linear Generative Model for Graph Structure.- Graph Seriation Using Semi-definite Programming.- Comparing String Representations and Distances in a Natural Images Classification Task.- Reduction Strings: A Representation of Symbolic Hierarchical Graphs Suitable for Learning.- Combinatorial Maps.- Representing and Segmenting 2D Images by Means of Planar Maps with Discrete Embeddings: From Model to Applications.- Inside and Outside Within Combinatorial Pyramids.- The GeoMap: A Unified Representation for Topology and Geometry.- Pyramids of n-Dimensional Generalized Maps.- Matching.- Towards Unitary Representations for Graph Matching.- A Direct Algorithm to Find a Largest Common Connected Induced Subgraph of Two Graphs.- Reactive Tabu Search for Measuring Graph Similarity.- Tree Matching Applied to Vascular System.- Hierarchical Graph Abstraction and Matching.- A Graph-Based, Multi-resolution Algorithm for Tracking Objects in Presence of Occlusions.- Coarse-to-Fine Object Recognition Using Shock Graphs.- Adaptive Pyramid and Semantic Graph: Knowledge Driven Segmentation.- A Graph-Based Concept for Spatiotemporal Information in Cognitive Vision.- Inexact Graph Matching.- Approximating the Problem, not the Solution: An Alternative View of Point Set Matching.- Defining Consistency to Detect Change Using Inexact Graph Matching.- Asymmetric Inexact Matching of Spatially-Attributed Graphs.- From Exact to Approximate Maximum Common Subgraph.- Learning.- Automatic Learning of Structural Models of Cartographic Objects.- An Experimental Comparison of Fingerprint Classification Methods Using Graphs.- Collaboration Between Statistical and Structural Approaches for Old Handwritten Characters Recognition.- Graph Sequences.- Decision Trees for Error-Tolerant Graph Database Filtering.- Recovery of Missing Information in Graph Sequences.- Tree-Based Tracking of Temporal Image.- Graph Kernels.- Protein Classification with Kernelized Softassign.- Local Entropic Graphs for Globally-Consistent Graph Matching.- Edit Distance Based Kernel Functions for Attributed Graph Matching.- Graphs and Heat Kernels.- A Robust Graph Partition Method from the Path-Weighted Adjacency Matrix.- Recent Results on Heat Kernel Embedding of Graphs.

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