Graph-Based Representations in Pattern Recognition, Kartoniert / Broschiert
Graph-Based Representations in Pattern Recognition
- 14th IAPR-TC-15 International Workshop, GbRPR 2025, Caen, France, June 25-27, 2025, Proceedings
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Luc Brun, Vincenzo Carletti, Sébastien Bougleux, Benoît Gaüzère
- Verlag:
- Springer, 06/2025
- Einband:
- Kartoniert / Broschiert
- Sprache:
- Englisch
- ISBN-13:
- 9783031941382
- Artikelnummer:
- 12316213
- Umfang:
- 292 Seiten
- Gewicht:
- 446 g
- Maße:
- 235 x 155 mm
- Stärke:
- 16 mm
- Erscheinungstermin:
- 8.6.2025
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
.- 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.