Machine Learning Based Air (24 results)

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

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Hardback. Condition: New. 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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Hardback. Condition: New. 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.…

Taschenbuch. Condition: Neu. Neuware - This book presents cutting-edge, effective methods of artificial intelligence and machine learning for data modeling, with applications to the important and challenging area of air pollution. Both classical stochastic and tree-based ensemble learning approaches and their hybrid combinations are considered, including: ARIMA, Temporal Causal Modeling, wavelet transforms, Classification and Regression Trees (CART), Multivariate Adaptive Regression Splines (MARS), Random Forests, and Adaptively Resampling and Combining (Arcing). The selected methods require minimal computer resources (execution time and memory) and are oriented for inclusion in distributed environments and mobile devices. In addition, the book emphasizes the statistically correct construction and investigation of the problems under consideration and detailed analysis of model errors, rather than presenting statistical theory or ready-made codes from software packages. The indicated approaches have been demonstrated to forecast time series of air pollutants such as particulate matter, sulfur dioxide, nitrogen dioxide, and others, depending on a small number of rapidly changing meteorological and atmospheric factors. The methods and frameworks are applied to empirical data from several cities in Bulgaria. The results of the individual applications are presented in five chapters as case studies. These studies demonstrate in detail the steps of the developed approaches for modeling and forecasting of real measured data related to urban air pollution. The book has the potential to serve not only as a systematic introduction to the selected ensemble learning methods for time series, but also as a tool and guide for building adequate and statistically valid forecasting models.…

Hardback. Condition: New. 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.…

Hardcover. Condition: Brand New. 344 pages. 9.02x5.99x9.02 inches. In Stock.

Condition: New. 2026. hardcover. . . . . . Books ship from the US and Ireland.

Hardback. Condition: New. 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.…

Condition: New. 2026. hardcover. . . . . .

Hardcover. Condition: Brand New. 344 pages. 9.02x5.99x9.02 inches. In Stock. This item is printed on demand.

Hardcover. Condition: new. Hardcover. 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. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Condition: New. PRINT ON DEMAND.

Buch. Condition: Neu. Machine Learning Based Air Traffic Surveillance System Using Image Processing | Jay Kumar Pandey | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Emerald Group Publishing Limited | EAN 9781805920632 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…