Advances in Computers, Volume presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Copyright - p. iii 5. Contributors - p. iii 6. Preface - p. xi 7. Chapter One: AI and machine learning for real-world problems - p. 1 8. Chapter Two: Survey of graph neural network for learning complex problems - p. 13 9. Chapter Three: Adaptive software platform architecture for aerial vehicle safety levels in real-world applications - p. 51 10. Chapter Four: OODA loop for learning open-world novelty problems - p. 97 11. Chapter Five: Privacy-aware crowd counting methods for real-world environment - p. 131 12. Chapter Six: AI and machine learning for computer vision applications in open world - p. 169 13. Chapter Seven: PIM hardware accelerators for real-world problems - p. 225 14. Chapter Eight: Irregular situations in real-world intelligent systems - p. 253 15. Chapter Nine: Offline reinforcement learning methods for real-world problems - p. 285 16. Chapter Ten: Addressing uncertainty challenges for autonomous driving in real-world environments - p. 317
Advances in Computers, Volume presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Copyright - p. iii 5. Contributors - p. iii 6. Preface - p. xi 7. Chapter One: AI and machine learning for real-world problems - p. 1 8. Chapter Two: Survey of graph neural network for learning complex problems - p. 13 9. Chapter Three: Adaptive software platform architecture for aerial vehicle safety levels in real-world applications - p. 51 10. Chapter Four: OODA loop for learning open-world novelty problems - p. 97 11. Chapter Five: Privacy-aware crowd counting methods for real-world environment - p. 131 12. Chapter Six: AI and machine learning for computer vision applications in open world - p. 169 13. Chapter Seven: PIM hardware accelerators for real-world problems - p. 225 14. Chapter Eight: Irregular situations in real-world intelligent systems - p. 253 15. Chapter Nine: Offline reinforcement learning methods for real-world problems - p. 285 16. Chapter Ten: Addressing uncertainty challenges for autonomous driving in real-world environments - p. 317
