Description
Book SynopsisChapter 1 Applications of Graph Neural Networks in Computer Vision: Transforming Perception Through Structure.- Chapter 2 Large-Scale Learnable Graph Convolutional Networks (LGCNs) Graph Neural Networks (GNNs): Articulating the Advancements and Advantages, Graph Neural Networks (GNNs): the Essentials and the Use Cases.- Chapter 3 Deep Finance: Harnessing Graph-Based Neural Networks for Market Predictions.- Chapter 4 Illustrating the significance of graphical neural networks to prevent social engineering.- Chapter 5 The Challenges of Graph Neural Networks.- Chapter 6 Utilizing Graph Neural Networks (GNN) in Quantum-Natural Language Processing (Q-NLP) for Risk Management in Banking Sector: A Novel Approach.- Chapter 7 Graph Neural Networks (GNNs) Applications.- Chapter 8 Revolutionizing AI: Applications of Graph Neural Networks Across Industries.- Chapter 9 Graph Neural Networks for Enhanced Computer Vision.- Chapter 10 Enhancing Natural Language Processing with Graph Neural Networks: Improving Understanding, Performance, and Transparency.- Chapter 11 Microarray Data Feature Selection and Classification Using Graph Neural Networks.- Chapter 12 Graph Neural Network.- Chapter 13 Graph Neural Networks for Scene Understanding: A
Review and Future Directions.- Chapter 14 Graph Neural Networks: Architecting Intelligence Across Domains - From Molecular Design to Urban Systems.- Chapter 15 Unlocking Insights: A Guide to the Benefits of Graph-represented Data In Gnns.- Chapter 16 Graph Neural Networks Applications - A Dwell into Biomedical Applications and Traffic Flow Analysis.- Index.
