Machine Learning Based Air Traffic Surveillance System Using Image Processing
eBook - ePub

Machine Learning Based Air Traffic Surveillance System Using Image Processing

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Machine Learning Based Air Traffic Surveillance System Using Image Processing

About this book

Machine Learning Based Air Traffic Surveillance System Using Image Processing analyses how advanced machine learning algorithms and image processing technologies are revolutionising air-traffic management. By integrating real-time visual data analysis with sophisticated artificial intelligence techniques, this book highlights the potential to enhance situational awareness, safety, and efficiency in managing increasingly complex and congested airspaces. It delves into the use of convolutional neural networks (CNNs) and deep learning models to identify, track, and analyse aircraft movements, offering precise and actionable insights for air-traffic controllers.

This comprehensive resource combines theoretical foundations with practical applications, including real-world case studies and discussions on system implementation. It addresses critical aspects such as object detection, anomaly identification, and trajectory prediction, alongside regulatory, ethical, and cybersecurity considerations. With its blend of cutting-edge research and practical insights, this book is an invaluable guide for professionals, researchers, and students in aerospace engineering, artificial intelligence, and computer vision, providing a roadmap for advancing air-traffic surveillance and management in the era of intelligent systems.

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Yes, you can access Machine Learning Based Air Traffic Surveillance System Using Image Processing by Jay Kumar Pandey,Mritunjay Rai,Faizan Ahmad in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Computer Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Halftitle
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. List of Abbreviations and Acronyms
  8. About the Editors
  9. About the Contributors
  10. Foreword
  11. Preface
  12. Acknowledgments
  13. Chapter 1 Advanced Image Processing Techniques for Smart Air Traffic Monitoring
  14. Chapter 2 Explainable AI (XAI) in Air Traffic Monitoring Systems
  15. Chapter 3 Machine Learning and Image Processing Integration Air Traffic
  16. Chapter 4 Image Processing Techniques in Sovan Air Traffic Monitoring
  17. Chapter 5 AI-powered Satellite Imagery Processing for Global Air Traffic Surveillance
  18. Chapter 6 Advanced AI-enabled UAV Swarms for Real-time Air Traffic Surveillance
  19. Chapter 7 A Robust Intelligent Framework for Air Traffic Management System Using Machine Learning
  20. Chapter 8 Factoring Explainability and Transparency in Machine Learning-based Air Traffic Surveillance
  21. Chapter 9 Enhancing Air Traffic Surveillance with Machine Learning
  22. Chapter 10 AI-powered Satellite Image Processing for Global Air Traffic Surveillance Techniques Using NCNN–EGSA Optimization Techniques
  23. Chapter 11 Optimization of Airspace Using Pigeon Feather Flight Path Optimization (PFO) Algorithm in India
  24. Chapter 12 Enhancing IoT Surveillance Systems Using DL and Big Data for Advanced Security Protocols
  25. Chapter 13 Leveraging AI and IoT for Advanced Air Traffic Surveillance and Collision Avoidance
  26. Chapter 14 Exploring the Use of AI in the Aviation Sector: A Comprehensive Bibliographic Evaluation
  27. Index