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001476380 001__ 1476380
001476380 003__ OCoLC
001476380 005__ 20231003174646.0
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001476380 008__ 230830s2023\\\\sz\a\\\\o\\\\\101\0\eng\d
001476380 019__ $$a1395178484$$a1395181236
001476380 020__ $$a9783031427954$$q(electronic bk.)
001476380 020__ $$a3031427955$$q(electronic bk.)
001476380 020__ $$z9783031427947$$q(print)
001476380 020__ $$z3031427947
001476380 0247_ $$a10.1007/978-3-031-42795-4$$2doi
001476380 035__ $$aSP(OCoLC)1395544726
001476380 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dOCLCQ$$dOCLCO
001476380 049__ $$aISEA
001476380 050_4 $$aTK7882.P3
001476380 08204 $$a006.3$$223/eng/20230830
001476380 1112_ $$aIAPR-TC15 Workshop on Graph-Based Representations in Pattern Recognition$$n(13th :$$d2023 :$$cVietri sul Mare, Italy)
001476380 24510 $$aGraph-based representations in pattern recognition :$$b13th IAPR-TC-15 International Workshop, GbRPR 2023, Vietri sul Mare, Italy, September 6-8, 2023, Proceedings /$$cMario Vento, Pasquale Foggia, Donatello Conte, Vincenzo Carletti, editors.
001476380 2463_ $$aGbRPR 2023
001476380 264_1 $$aCham, Switzerland :$$bSpringer,$$c2023.
001476380 300__ $$a1 online resource (xvi, 184 pages) :$$billustrations (some color).
001476380 336__ $$atext$$btxt$$2rdacontent
001476380 337__ $$acomputer$$bc$$2rdamedia
001476380 338__ $$aonline resource$$bcr$$2rdacarrier
001476380 4901_ $$aLecture notes in computer science,$$x1611-3349 ;$$v14121
001476380 500__ $$aIncludes author index.
001476380 5050_ $$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.
001476380 506__ $$aAccess limited to authorized users.
001476380 520__ $$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.
001476380 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed August 30, 2023).
001476380 650_0 $$aPattern recognition systems$$vCongresses.
001476380 650_0 $$aComputer vision$$vCongresses.
001476380 650_0 $$aGraph theory$$vCongresses.
001476380 650_6 $$aReconnaissance des formes (Informatique)$$vCongrès.
001476380 650_6 $$aVision par ordinateur$$vCongrès.
001476380 655_0 $$aElectronic books.
001476380 7001_ $$aVento, Mario,$$d1960-$$eeditor.$$1https://orcid.org/0000-0002-2948-741X
001476380 7001_ $$aFoggia, P.$$q(Pasquale),$$eeditor.$$1https://orcid.org/0000-0002-7096-1902
001476380 7001_ $$aConte, Donatello,$$eeditor.$$1https://orcid.org/0000-0003-4642-4768
001476380 7001_ $$aCarletti, Vincenzo,$$eeditor.$$0(orcid)0000-0002-9130-5533$$1https://orcid.org/0000-0002-9130-5533
001476380 77608 $$iPrint version:$$aVento, Mario$$tGraph-Based Representations in Pattern Recognition$$dCham : Springer,c2023$$z9783031427947
001476380 830_0 $$aLecture notes in computer science ;$$v14121.$$x1611-3349
001476380 852__ $$bebk
001476380 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-42795-4$$zOnline Access$$91397441.1
001476380 909CO $$ooai:library.usi.edu:1476380$$pGLOBAL_SET
001476380 980__ $$aBIB
001476380 980__ $$aEBOOK
001476380 982__ $$aEbook
001476380 983__ $$aOnline
001476380 994__ $$a92$$bISE