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 ...
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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.
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Add this copy of Generative Adversarial Learning: Architectures and to cart. $187.87, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2023 by Springer Nature Switzerland AG.
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New. Contains: Illustrations, black & white, Illustrations, color. Intelligent Systems Reference Library . XIV, 355 p. 145 illus., 132 illus. in color. Intended for professional and scholarly audience.
Add this copy of Generative Adversarial Learning: Architectures and to cart. $187.87, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2022 by Springer Nature Switzerland AG.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. 355 p. Intelligent Systems Reference Library , 217. 132 Illustrations, color; 13 Illustrations, black and white; XIV, 355 p. 145 illus., 132 illus. in color. Intended for professional and scholarly audience.