附註:Includes bibliographical references and index.
Chapter 1. Conceptualising the role of intellectual property and ethical behaviour in artificial intelligence -- Chapter 2. Measuring throughput and latency of machine learning techniques for intrusion detection -- Chapter 3. Securing digital ecosystems: harnessing the power of intelligent machines in a secure and sustainable environment -- Chapter 4. IoT-based economic flame detection device for safety -- Chapter 5. Human face mask detection using YOLOv7CBAM in deep learning -- Chapter 6. The role of AI in improving interaction with cultural heritage: an overview -- Chapter 7. Machine learning approach for robot navigation using motor imagery signals -- Chapter 8. Cloud solutions for smart parking and traffic control in smart cities -- Chapter 9. Building sustainable smart cities through cloud and intelligent parking system -- Chapter 10. A study on AI and blockchain-powered smart parking models for urban mobility -- Chapter 11. Machine learning and deep learning for intelligent systems in small aircraft applications -- Chapter 12. Machine learning in e-health and digital healthcare: practical strategies for transformation -- Chapter 13. Unsupervised learning techniques for vibration-based structural health monitoring systems driven by data: a general overview -- Chapter 14. Convergence of data science-AI-green chemistry-affordable medicine: transforming drug discovery -- Chapter 15. Intelligent machines, IoT, and AI in revolutionizing agriculture for water processing -- Chapter 16. A mixture model for fruit ripeness identification in deep learning -- Chapter 17. YOLO models for fresh fruit classification from digital videos.
摘要:"The Handbook of Research on AI and ML for Intelligent Machines and Systems offers a comprehensive exploration of the pivotal role played by artificial intelligence (AI) and machine learning (ML) technologies in the development of intelligent machines. As the demand for intelligent machines continues to rise across various sectors, understanding the integration of these advanced technologies becomes paramount. While AI and ML have individually showcased their capabilities in developing robust intelligent machine systems and services, their fusion holds the key to propelling intelligent machines to a new realm of transformation. By compiling recent advancements in intelligent machines that rely on machine learning and deep learning technologies, this book serves as a vital resource for researchers, graduate students, PhD scholars, faculty members, scientists, and software developers. It offers valuable insights into the key concepts of AI and ML, covering essential security aspects, current trends, and often overlooked perspectives that are crucial for achieving comprehensive understanding. It not only explores the theoretical foundations of AI and ML but also provides guidance on applying these techniques to solve real-world problems. Unlike traditional texts, it offers flexibility through its distinctive module-based structure, allowing readers to follow their own learning paths."--
