LEADER 06663nam 22008535 450 001 9910484584103321 005 20200705080526.0 010 $a3-319-18224-2 024 7 $a10.1007/978-3-319-18224-7 035 $a(CKB)3710000000416822 035 $a(SSID)ssj0001501499 035 $a(PQKBManifestationID)11848049 035 $a(PQKBTitleCode)TC0001501499 035 $a(PQKBWorkID)11447121 035 $a(PQKB)10490990 035 $a(DE-He213)978-3-319-18224-7 035 $a(MiAaPQ)EBC6283237 035 $a(MiAaPQ)EBC5587335 035 $a(Au-PeEL)EBL5587335 035 $a(OCoLC)909023169 035 $a(PPN)186029586 035 $a(EXLCZ)993710000000416822 100 $a20150504d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aGraph-Based Representations in Pattern Recognition $e10th IAPR-TC-15 International Workshop, GbRPR 2015, Beijing, China, May 13-15, 2015. Proceedings /$fedited by Cheng-Lin Liu, Bin Luo, Walter G. Kropatsch, Jian Cheng 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (XII, 376 p. 110 illus.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v9069 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-18223-4 327 $aGraph-based Representation -- Approximation of Graph Edit Distance in Quadratic Time -- Data Graph Formulation as the Minimum-Weight Maximum-Entropy Problem -- An Entropic Edge Assortativity Measure -- A Subpath Kernel for Learning Hierarchical Image Representations -- Coupled-Feature Hypergraph Representation for Feature Selection -- Reeb Graphs Through Local Binary Patterns -- Incremental embedding within a dissimilarity-based framework -- Graph Matching -- A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching -- Consensus of Two Graph Correspondences through a Generalisation of the Bipartite Graph Matching Algorithm -- Revisiting Volegnant-Jonker for Approximating Graph Edit Distance -- A Hypergraph Matching Framework for Refining Multi-source Feature Correspondences -- Kite Recognition by means of Graph Matching -- GEM++: a tool for solving substitution-tolerant subgraph isomorphism -- A Graph Database Repository and Performance Evaluation Metrics for Graph Edit Distance -- Improving Hausdorff Edit Distance Using Structural Node Context -- Learning Graph Model for Different Dimensions Image Matching -- VF2 Plus: An Improved Version of VF2 For Biological Graphs -- Report on the First Contest on Graph Matching Algorithms for Pattern Search in Biological Databases -- Approximate Graph Edit Distance Computation Combining Bipartite Matching and Exact Neighborhood Substructure Distance -- Multi-layer Tree Matching Using HSTs -- Large-scale Graph Indexing using Binary Embeddings of Node Contexts -- Attributed Relational Graph Matching with Sparse Relaxation and Bistochastic Normalization -- Graph Clustering and Classification.-On the Influence of Node Centralities on Graph Edit Distance for Graph Classification -- A Mixed Weisfeiler-Lehman Graph Kernel -- A Quantum Jensen-Shannon Graph Kernel using Discrete-time Quantum Walks -- Density Based Cluster Extension and Dominant Sets Clustering -- Salient Object Segmentation from Stereoscopic Images -- Causal Video Segmentation using Superseeds and Graph Matching -- Fast Minimum Spanning Tree based Clustering Algorithms on Local Neighborhood Graph -- Graph-based Application -- From bags to graphs of stereo subgraphs in order to predict molecule's properties -- Thermodynamics of Time Evolving Networks -- Isometric Mapping Hashing -- Skeletal Graphs from Schrodinger Magnitude and Phase -- Graph Based Lymphatic Vessel Wall Localisation and Tracking -- A Comic Retrieval System Based on Multilayer Graph Representation and Graph Mining -- Learning High-Order Structures for Texture Retrieval. 330 $aThis book constitutes the refereed proceedings of the 10th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2015, held in Beijing, China, in May 2015. The 36 papers presented in this volume were carefully reviewed and selected from 53 submissions. The accepted papers cover diverse issues of graph-based methods and applications, with 7 in graph representation, 15 in graph matching, 7 in graph clustering and classification, and 7 in graph-based applications. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;$v9069 606 $aPattern recognition 606 $aOptical data processing 606 $aComputer graphics 606 $aComputer science?Mathematics 606 $aData structures (Computer science) 606 $aAlgorithms 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aComputer Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22013 606 $aDiscrete Mathematics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17028 606 $aData Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I15017 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 615 0$aPattern recognition. 615 0$aOptical data processing. 615 0$aComputer graphics. 615 0$aComputer science?Mathematics. 615 0$aData structures (Computer science). 615 0$aAlgorithms. 615 14$aPattern Recognition. 615 24$aImage Processing and Computer Vision. 615 24$aComputer Graphics. 615 24$aDiscrete Mathematics in Computer Science. 615 24$aData Structures. 615 24$aAlgorithm Analysis and Problem Complexity. 676 $a006.4 702 $aLiu$b Cheng-Lin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLuo$b Bin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKropatsch$b Walter G$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aCheng$b Jian$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484584103321 996 $aGraph-Based Representations in Pattern Recognition$9772063 997 $aUNINA