附註:Includes bibliographical references and index.
Chapter 1. Fundamentals of graph for graph neural network -- Chapter 2. Graph neural network and its applications -- Chapter 3. Introduction to graph neural network: types and applications -- Chapter 4. Graph classification of graphneural networks -- Chapter 5. Adversarial attacks on graph neural network: techniques and countermeasures -- Chapter 6. Fundamental concepts in graph attention networks -- Chapter 7. Graph convolutional neural networks for link prediction in social networks -- Chapter 8. Study and analysis of visual saliency applications using graph neural networks -- Chapter 9. Application and some fundamental study of GNN in forecasting -- Chapter 10. Applications of GNNs and m-health for disease tracking -- Chapter 11. A comprehensive study on student academic performance predictions using graph neural network -- Chapter 12. Methods and applications of graph neural networks for fake news detection using AI-inspired algorithms -- Chapter 13. Comprehensive study of face recognition using feature extraction and fusion face technique.
摘要:"This book will aim to provide stepwise discussion; exhaustive literature review; detailed analysis and discussion; rigorous experimentation results, application-oriented approach that will be demonstrated with respect to applications of Graph Neural Network (GNN). It will be written to develop the understanding of concepts and techniques on GNN and to establish the familiarity of different real applications in various domains for GNN. Moreover, it will also cover theprevailing challenges and opportunities"--
