9789813360501 - generative adversarial networks for image generation di mao, xudong; li, qing (12 risultati)
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Da: Better World Books: West, Reno, NV, U.S.A.Better World Books: West
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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: Springer, Berlin|Springer Nature Singapore|Springer, 2022
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Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore, 2022
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Generative adversarial networks (GANs)were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook's AI research director) as 'the most interesting idea in the last 10 years in…ML.' GANs' potential is huge, because they can learn to mimic any distribution of data, which means they can be taught to create worlds similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and theiroutput is remarkable- poignant even. In 2018, Christie's sold a portrait that had been generated by a GAN for $432,000.Although image generation has been challenging, GAN image generation has proved to be very successful and impressive. However, there are two remaining challenges for GAN image generation: the quality of the generated image and the training stability. This book first provides an overview of GANs, and then discusses the task of image generation and the detailsof GAN image generation. It also investigates a number of approaches to address the two remaining challenges for GAN image generation. Additionally, it explores three promising applications of GANs, including image-to-image translation, unsupervised domain adaptation and GANs for security. This book appeals to students and researchers who are interested in GANs, image generation and general machine learning and computer vision.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Generative adversarial networks (GANs)were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook's AI research director) as 'the most interesting idea in the l…ast 10 years in ML.' GANs' potential is huge, because they can learn to mimic any distribution of data, which means they can be taught to create worlds similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and theiroutput is remarkable- poignant even. In 2018, Christie's sold a portrait that had been generated by a GAN for $432,000.Although image generation has been challenging, GAN image generation has proved to be very successful and impressive. However, there are two remaining challenges for GAN image generation: the quality of the generated image and the training stability. This book first provides an overview of GANs, and then discusses the task of image generation and the detailsof GAN image generation. It also investigates a number of approaches to address the two remaining challenges for GAN image generation. Additionally, it explores three promising applications of GANs, including image-to-image translation, unsupervised domain adaptation and GANs for security. This book appeals to students and researchers who are interested in GANs, image generation and general machine learning and computer vision. 92 pp. Englisch.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Generative Adversarial Networks for Image Generation | Xudong Mao (u. a.) | Taschenbuch | xii | Englisch | 2022 | Springer | EAN 9789813360501 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu P…rint on Demand.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Generative adversarial networks (GANs) were introduced by Ian Goodfellow and his co-authors including Yoshua Bengio in 2014, and were to referred by Yann Lecun (Facebook's AI research director) as 'the most interesting idea in the last… 10 years in ML.' GANs' potential is huge, because they can learn to mimic any distribution of data, which means they can be taught to create worlds similar to our own in any domain: images, music, speech, prose. They are robot artists in a sense, and their output is remarkable - poignant even. In 2018, Christie's sold a portrait that had been generated by a GAN for $432,000.Although image generation has been challenging, GAN image generation has proved to be very successful and impressive. However, there are two remaining challenges for GAN image generation: the quality of the generated image and the training stability. This book first provides an overview of GANs, and then discusses the task of image generation and the detailsof GAN image generation. It also investigates a number of approaches to address the two remaining challenges for GAN image generation. Additionally, it explores three promising applications of GANs, including image-to-image translation, unsupervised domain adaptation and GANs for security. This book appeals to students and researchers who are interested in GANs, image generation and general machine learning and computer vision.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 92 pp. Englisch.
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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