Graph-based representations in patte...
GbRPR (Workshop) (2025 :)

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  • Graph-based representations in pattern recognition = 14th IAPR-TC-15 International Workshop, GbRPR 2025, Caen, France, June 25-27, 2025 : proceedings /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Graph-based representations in pattern recognition/ edited by Luc Brun ... [et al.].
    其他題名: 14th IAPR-TC-15 International Workshop, GbRPR 2025, Caen, France, June 25-27, 2025 : proceedings /
    其他題名: IAPR-TC-15
    其他作者: Brun, Luc.
    團體作者: GbRPR (Workshop)
    出版者: Cham :Springer Nature Switzerland : : 2025.,
    面頁冊數: xi, 278 p. :ill. (some col.), digital ;24 cm.
    內容註: Cybersecurity based on Graph models. -- A Modular Triple Exchange Co-learning Framework for Anomaly Detection in Scarcely Labeled Graph Data. -- Advanced Malware Detection in Code Repositories Using Graph Neural Network. -- Resistance Distance Guided Node Injection Attack on Graph Neural Network. -- Graph based bioinformatics. -- Gene Co-Expression Networks Are Poor Proxies for Expert-Curated Gene Regulatory Networks. -- Graph Neural Network Based on Molecular and Pharmacophoric Features for Drug Design Applications. -- Graph-Based Representations of Almost Constant Graphs for Nanotoxicity Prediction. -- Label Modulated Dynamic Graph Convolution for Subcellular Structure Segmentation from Nanoscopy Image. -- Insights on Using Graph Neural Networks for Sulcal Graphs Predictive Models. -- Graph Neural Networks for Multimodal Brain Connectivity Analysis in Multiple Sclerosis. -- Graph similarities and graph patterns. -- A Geometric Perspective on Graph Similarity Learning using Convex Hulls. -- VF-GPU: Exploiting Parallel GPU Architectures to Solve Subgraph Isomorphis. -- Grammatical Path Network: Unveiling Cycles Through Path Computation. -- Deep QMiner: Towards a generalized DeepQ-Learning Approach for Graph Pattern Mining. -- GNN: shortcomings and solutions. -- An Empirical Investigation of Shortcuts in Graph Learning. -- A General Sampling Framework for Graph Convolutional Network Training. -- Fusion of GNN and GBDT Models for Graph and Node Classification. -- Harnessing GraphSAGE for Learning Representations of Massive Transactional networks. -- Entropy-Guided Graph Clustering via Rényi Optimization. -- Graph learning and computer vision. -- Exploring a Graph Regression Problem in River Networks. -- Saliency Matters: from nodes to objects. -- Hierarchical super-pixels graph neural networks for image semantic segmentation. -- Lifting some Secrets about Contrast Pyramids. -- An Evolution Equation Involving the Generalized Biased Infinity Laplacian on Graphs. -- Doc2Graph-X: A Multilingual Graph-Based Framework for Form Understanding. -- VisHubGAT: Visible Connectivity and Hub Nodes for Multimodal Entity Extraction.
    Contained By: Springer Nature eBook
    標題: Pattern recognition systems - Congresses. -
    電子資源: https://doi.org/10.1007/978-3-031-94139-9
    ISBN: 9783031941399
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