Combining visual intelligence federated (23 risultati)

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

Condizione: New.

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

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Hardback. Condizione: New.

Paperback. Condizione: New.

Hardback. Condizione: New.

Paperback. Condizione: new. Paperback. Smart devices in healthcare can interact with the environment by gathering, processing, interpreting, storing, and retrieving information originated from sensors, neuromorphic analog circuits, robots, and other data retrieving sources through explainable AI, Internet of Things, gestural technology, and federated learning. These systems can utilize visual languages to improve communication with people in real-life scenarios, such as intelligent devices which recognize patterns. Such languages, combined with intelligent, experience-based, healthcare systems, fall in the area of visual intelligence, empowering people to understand how machines process the data smart healthcare devices. The combination of smart healthcare and visual intelligence with federated learning may give rise to new applications in fields as diverse as healthcare, education, marketing, gaming, and automation. Combining Visual Intelligence and Federated Learning in Smart Healthcare explores research areas that connect visual information processing with intelligence, federated learning, and the Internet of Things, promoting their integration and exciting new developments. It examines theories, practices, and experiences in the field of smart healthcare for visual intelligence with federated learning. This book covers topics such as artificial intelligence, predictive analytics, and smart technology, and is a useful resource for medical professionals, business owners, healthcare workers, computer engineers, data scientists, academicians, and researchers. "The objective of this book aims to implement emerging technology to transforms images from the original grayscale and reveals hidden patterns, into new well-defined structured patterns empowering research community, and computer analytics to remove indicative uncertainty"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Hardcover. Condizione: new. Hardcover. Smart devices in healthcare can interact with the environment by gathering, processing, interpreting, storing, and retrieving information originated from sensors, neuromorphic analog circuits, robots, and other data retrieving sources through explainable AI, Internet of Things, gestural technology, and federated learning. These systems can utilize visual languages to improve communication with people in real-life scenarios, such as intelligent devices which recognize patterns. Such languages, combined with intelligent, experience-based, healthcare systems, fall in the area of visual intelligence, empowering people to understand how machines process the data smart healthcare devices. The combination of smart healthcare and visual intelligence with federated learning may give rise to new applications in fields as diverse as healthcare, education, marketing, gaming, and automation. Combining Visual Intelligence and Federated Learning in Smart Healthcare explores research areas that connect visual information processing with intelligence, federated learning, and the Internet of Things, promoting their integration and exciting new developments. It examines theories, practices, and experiences in the field of smart healthcare for visual intelligence with federated learning. This book covers topics such as artificial intelligence, predictive analytics, and smart technology, and is a useful resource for medical professionals, business owners, healthcare workers, computer engineers, data scientists, academicians, and researchers. "The objective of this book aims to implement emerging technology to transforms images from the original grayscale and reveals hidden patterns, into new well-defined structured patterns empowering research community, and computer analytics to remove indicative uncertainty"-- Provided by publisher. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Smart devices in healthcare can interact with the environment by gathering, processing, interpreting, storing, and retrieving information originated from sensors, neuromorphic analog circuits, robots, and other data retrieving sources through explainable AI, Internet of Things, gestural technology, and federated learning. These systems can utilize visual languages to improve communication with people in real-life scenarios, such as intelligent devices which recognize patterns. Such languages, combined with intelligent, experience-based, healthcare systems, fall in the area of visual intelligence, empowering people to understand how machines process the data smart healthcare devices. The combination of smart healthcare and visual intelligence with federated learning may give rise to new applications in fields as diverse as healthcare, education, marketing, gaming, and automation. Combining Visual Intelligence and Federated Learning in Smart Healthcare explores research areas that connect visual information processing with intelligence, federated learning, and the Internet of Things, promoting their integration and exciting new developments. It examines theories, practices, and experiences in the field of smart healthcare for visual intelligence with federated learning. This book covers topics such as artificial intelligence, predictive analytics, and smart technology, and is a useful resource for medical professionals, business owners, healthcare workers, computer engineers, data scientists, academicians, and researchers.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Smart devices in healthcare can interact with the environment by gathering, processing, interpreting, storing, and retrieving information originated from sensors, neuromorphic analog circuits, robots, and other data retrieving sources through explainable AI, Internet of Things, gestural technology, and federated learning. These systems can utilize visual languages to improve communication with people in real-life scenarios, such as intelligent devices which recognize patterns. Such languages, combined with intelligent, experience-based, healthcare systems, fall in the area of visual intelligence, empowering people to understand how machines process the data smart healthcare devices. The combination of smart healthcare and visual intelligence with federated learning may give rise to new applications in fields as diverse as healthcare, education, marketing, gaming, and automation. Combining Visual Intelligence and Federated Learning in Smart Healthcare explores research areas that connect visual information processing with intelligence, federated learning, and the Internet of Things, promoting their integration and exciting new developments. It examines theories, practices, and experiences in the field of smart healthcare for visual intelligence with federated learning. This book covers topics such as artificial intelligence, predictive analytics, and smart technology, and is a useful resource for medical professionals, business owners, healthcare workers, computer engineers, data scientists, academicians, and researchers.…

Condizione: New. PRINT ON DEMAND.