9781839537578 - federated learning for multimedia data processing and security in industry 5.0 (computing and networks) de srivastava, gautam (15 resultados)
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2025
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Editorial: The Institution of Engineering and Technology, 2025
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Editorial: The Institution of Engineering and Technology, 2025
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 129,96
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Editorial: Institution of Engineering and Technology, GB, 2025
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
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EUR 145,59
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Hardback. Condición: New. Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for m…ission critical applications. Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data. The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond. Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2025
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Condición: As New. Unread book in perfect condition.
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Editorial: The Institution of Engineering and Technology, 2025
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Editorial: The Institution of Engineering and Technology, 2025
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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Condición: New. In.
Idioma: Inglés
Editorial: Institution of Engineering and Technology, GB, 2025
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 180,49
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Hardback. Condición: New. Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for m…ission critical applications. Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data. The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond. Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.
Federated Learning for Multimedia Data Processing and Security in Industry 5.0
Srivastava, Gautam (Editor)/ Gadekallu, Thippa Reddy (Editor)
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 171,97
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Hardcover. Condición: Brand New. 350 pages. 9.21x6.14x9.21 inches. In Stock.
Idioma: Inglés
Editorial: Institution of Engineering and Technology, GB, 2025
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
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EUR 147,96
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Hardback. Condición: New. Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for m…ission critical applications. Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data. The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond. Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.
Idioma: Inglés
Editorial: Institution of Engineering and Technology, GB, 2025
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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EUR 169,94
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Hardback. Condición: New. Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for m…ission critical applications. Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data. The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond. Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.
Idioma: Inglés
Editorial: Institution Of Engineering & Technology Jan 2025, 2025
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 206,05
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Buch. Condición: Neu. Neuware - Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency… for mission critical applications. Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data. The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond. Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 162,81
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HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
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EUR 159,18
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Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
