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Verlag: Springer International Publishing, Springer International Publishing Feb 2023, 2023
ISBN 10: 3030913929 ISBN 13: 9783030913922
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs¿ theoretical developments and their applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch.
Verlag: Springer International Publishing, 2022
ISBN 10: 3030913899 ISBN 13: 9783030913892
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Verlag: Springer International Publishing, 2023
ISBN 10: 3030913929 ISBN 13: 9783030913922
Sprache: Englisch
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In den WarenkorbKartoniert / Broschiert. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents high-quality research articles addressing theoretical work for improving the learning process Provides a gentle introduction to GANs and related domainsDescribes most well-known GAN architectures and applications domains.
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ISBN 10: 3030913899 ISBN 13: 9783030913892
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents high-quality research articles addressing theoretical work for improving the learning process Provides a gentle introduction to GANs and related domainsDescribes most well-known GAN architectures and applications domains.
Verlag: Springer International Publishing, Springer Nature Switzerland Feb 2022, 2022
ISBN 10: 3030913899 ISBN 13: 9783030913892
Sprache: Englisch
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In den WarenkorbBuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs¿ theoretical developments and their applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 372 pp. Englisch.
Verlag: Springer International Publishing Feb 2023, 2023
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Verlag: Springer International Publishing Feb 2022, 2022
ISBN 10: 3030913899 ISBN 13: 9783030913892
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In den WarenkorbBuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a collection of recent research works addressing theoretical issues on improving the learning process and the generalization of GANs as well as state-of-the-art applications of GANs to various domains of real life. Adversarial learning fascinates the attention of machine learning communities across the world in recent years. Generative adversarial networks (GANs), as the main method of adversarial learning, achieve great success and popularity by exploiting a minimax learning concept, in which two networks compete with each other during the learning process. Their key capability is to generate new data and replicate available data distributions, which are needed in many practical applications, particularly in computer vision and signal processing. The book is intended for academics, practitioners, and research students in artificial intelligence looking to stay up to date with the latest advancements on GANs' theoretical developments and their applications. 372 pp. Englisch.
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