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Graph-based representations in pattern recognition = 13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6-8, 2023 : proceedings /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Graph-based representations in pattern recognition/ edited by Mario Vento ... [et al.].
其他題名:	13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6-8, 2023 : proceedings /
其他題名:	GbRPR 2023
其他作者:	Vento, Mario.
團體作者:	Workshop on the Preservation of Stability under Discretization
出版者:	Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:	xvi, 184 p. :ill. (some col.), digital ; : 24 cm.;
Contained By:	Springer Nature eBook
標題:	Artificial Intelligence. -
電子資源:	https://doi.org/10.1007/978-3-031-42795-4
ISBN:	9783031427954

Graph-based representations in pattern recognition = 13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6-8, 2023 : proceedings /
Graph-based representations in pattern recognition13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6-8, 2023 : proceedings /[electronic resource] :GbRPR 2023edited by Mario Vento ... [et al.]. - Cham :Springer Nature Switzerland :2023. - xvi, 184 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,141210302-9743 ;. - Lecture notes in computer science ;6140..

Graph 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.

This 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.

ISBN: 9783031427954

Standard No.: 10.1007/978-3-031-42795-4doiSubjects--Topical Terms:

646849
Artificial Intelligence.

LC Class. No.: TK7882.P3

Dewey Class. No.: 006.3

Graph-based representations in pattern recognition = 13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6-8, 2023 : proceedings /
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