Da: HPB-Red, Dallas, TX, U.S.A.
Paperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Lingua: Inglese
Editore: Manning Publications Co. LLC, 2019
ISBN 10: 1617295566 ISBN 13: 9781617295560
Da: Better World Books, Mishawaka, IN, U.S.A.
Condizione: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Lingua: Inglese
Editore: Manning, Shelter Island, NY, 2019
ISBN 10: 1617295566 ISBN 13: 9781617295560
Prima edizione
Paperback. Condizione: Very Good-. 1st Edition (Unstated). 7.38 X 0.4 X 9.25 inches; 214 pages; Light rubbing (shelf wear) to covers. Very Good condition otherwise. No other noteworthy defects. No markings. ; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be carefully cushioned in bubble wrap and securely boxed. All orders ship on the same or next business day. Buy with confidence.
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 245.
Da: Majestic Books, Hounslow, Regno Unito
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Revaluation Books, Exeter, Regno Unito
EUR 70,08
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Aggiungi al carrelloPaperback. Condizione: Brand New. pap/psc edition. 214 pages. 9.50x7.75x0.75 inches. In Stock.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032068116 ISBN 13: 9781032068114
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 82,68
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Aggiungi al carrelloPaperback. Condizione: New. This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio.A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc.Features:Presents a comprehensive guide on how to use GAN for images and videos.Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GANHighlights the inclusion of gaming effects using deep learning methodsExamines the significant technological advancements in GAN and its real-world application.Discusses as GAN challenges and optimal solutionsThe book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning.The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum.
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 74,22
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Condizione: New. pages cm First edition Includes bibliographical references and index.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
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Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: Brand New. 222 pages. 10.00x7.00x10.00 inches. In Stock.
Da: preigu, Osnabrück, Germania
EUR 65,80
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Generative Adversarial Networks and Deep Learning | Theory and Applications | Roshani Raut (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | Chapman and Hall/CRC | EAN 9781032068114 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Taylor and Francis Ltd, GB, 2024
ISBN 10: 1032068116 ISBN 13: 9781032068114
Da: Rarewaves.com UK, London, Regno Unito
EUR 77,71
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New. This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio.A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc.Features:Presents a comprehensive guide on how to use GAN for images and videos.Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GANHighlights the inclusion of gaming effects using deep learning methodsExamines the significant technological advancements in GAN and its real-world application.Discusses as GAN challenges and optimal solutionsThe book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning.The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 198,07
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Majestic Books, Hounslow, Regno Unito
EUR 204,70
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Aggiungi al carrelloCondizione: New. 223 pages.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 197,75
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 204,69
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Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days.