GANs in Action Deep learning with Generative Adversarial Networks

Generative Adversarial Networks, GANs, are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing". By pitting two neural networks against each other, one to generate fakes and one to spot them, GANs rapidly learn to produc...

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Detalles Bibliográficos
Otros Autores: Langr, Jakub, author (author), Bok, Vladimir, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Shelter Island, New York : Manning Publications 2021.
Edición:1st edition
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009822980906719
Descripción
Sumario:Generative Adversarial Networks, GANs, are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing". By pitting two neural networks against each other, one to generate fakes and one to spot them, GANs rapidly learn to produce photo-realistic faces and other media objects. With the potential to produce stunningly realistic animations or shocking deepfakes, GANs are a huge step forward in deep learning systems. "GANs in action" teaches you to build and train your own Generative Adversarial Networks. You'll start by creating simple generator and discriminator networks that are the foundation of GAN architecture. Then, following numerous hands-on examples, you'll train GANs to generate high-resolution images, image-to-image translation, and targeted data generation. Along the way, you'll find pro tips for making your system smart, effective, and fast.
Descripción Física:1 online resource (xxiii, 214 pages) : illustrations
Bibliografía:Includes bibliographical references and index.