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245 1 0 _aGraph-Based Representations in Pattern Recognition
_h[electronic resource] :
_b13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6–8, 2023, Proceedings /
_cedited by Mario Vento, Pasquale Foggia, Donatello Conte, Vincenzo Carletti.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXVI, 184 p. 33 illus., 27 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v14121
505 0 _aGraph Kernels and Graph Algorithms -- Quadratic Kernel Learning for Interpolation Kernel Machine Based Graph Classification -- Minimum Spanning Set Selection in Graph Kernels -- Graph-based vs. Vector-based Classification: A Fair Comparison -- A Practical Algorithm for Max-Norm Optimal Binary Labeling of Graphs -- Efficient Entropy-based Graph Kernel -- Graph Neural Networks -- GNN-DES: A new end-to-end dynamic ensemble selection method based on multi-label graph neural network -- C2N-ABDP: Cluster-to-Node Attention-based Differentiable Pooling -- Splitting Structural and Semantic Knowledge in Graph Autoencoders for Graph Regression -- Graph Normalizing Flows to Pre-image Free Machine Learning for Regression -- Matching-Graphs for Building Classification Ensembles -- Maximal Independent Sets for Pooling in Graph Neural Networks -- Graph-based Representations and Applications -- Detecting Abnormal Communication Patterns in IoT Networks Using Graph Neural Networks -- Cell segmentation of in situ transcriptomics data using signed graph partitioning -- Graph-based representation for multi-image super-resolution -- Reducing the Computational Complexity of the Eccentricity Transform -- Graph-Based Deep Learning on the Swiss River Network.
520 _aThis book constitutes the refereed proceedings of the 13th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2023, which took place in Vietri sul Mare, Italy, in September 2023. The 16 full papers included in this book were carefully reviewed and selected from 18 submissions. They were organized in topical sections on graph kernels and graph algorithms; graph neural networks; and graph-based representations and applications.
650 0 _aPattern recognition systems.
650 0 _aComputer science
_xMathematics.
650 0 _aDiscrete mathematics.
650 0 _aComputer graphics.
650 0 _aAlgorithms.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aArtificial intelligence.
650 1 4 _aAutomated Pattern Recognition.
650 2 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aComputer Graphics.
650 2 4 _aAlgorithms.
650 2 4 _aData Science.
650 2 4 _aArtificial Intelligence.
700 1 _aVento, Mario.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFoggia, Pasquale.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aConte, Donatello.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aCarletti, Vincenzo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783031427961
830 0 _aLecture Notes in Computer Science,
_x1611-3349 ;
_v14121
856 4 0 _uhttps://doi.org/10.1007/978-3-031-42795-4
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