Téléchargez le livre : Generative Adversarial Learning: Architectures and Applications

Generative Adversarial Learning: Architectures and Applications

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Springer


Paru le : 2022-02-07

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Description

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.
Pages
355 pages
Collection
n.c
Parution
2022-02-07
Marque
Springer
EAN papier
9783030913892
EAN EPUB
9783030913908
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
35
Taille du fichier
69857 Ko
Prix
179,34 €

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