Generative adversarial learning : architectures and applications / Roozbeh Razavi-Far, Ariel Ruiz-Garcia, Vasile Palade, Juergen Schmidhuber, editors.
Razavi-Far, Roozbeh.; Ruiz-Garcia, Ariel.; Palade, Vasile, 1964-; Schmidhuber, Jürgen.
2022
Q325.5
Available Online

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Title Generative adversarial learning : architectures and applications / Roozbeh Razavi-Far, Ariel Ruiz-Garcia, Vasile Palade, Juergen Schmidhuber, editors.
ISBN 9783030913908 (electronic bk.)
3030913902 (electronic bk.)
3030913899
9783030913892
DOI https://doi.org/10.1007/978-3-030-91390-8
Publication Details Cham, Switzerland : Springer, 2022.
Language English
Description 1 online resource.
Item Number 10.1007/978-3-030-91390-8 doi
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary 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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Digital File Characteristics text file PDF
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 23, 2022).
Added Author Razavi-Far, Roozbeh.
Ruiz-Garcia, Ariel.
Palade, Vasile, 1964-
Schmidhuber, Jürgen.
Series Intelligent systems reference library.
Available in Other Form Print version: 9783030913892
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All Resources
An Introduction to Generative Adversarial Learning: Architectures and Applications
Generative Adversarial Networks: A Survey on Training, Variants, and Applications
Fair Data Generation and Machine Learning through Generative Adversarial Networks.

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