Generative Adversarial Network

Principle and Practice

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,

Éditeur :

Springer


Paru le : 2026-02-02



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Description

This book
comprehensively and systematically introduces the theory of generative adversarial
networks and its applications in image and voice processing. This book consists
of 12 chapters, of which the first four chapters present basic knowledge,
including the principle of GAN, optimization objectives, training methods and
evaluation indicators. The last eight chapters introduce the applications of
GAN in various vertical fields, covering image generation, video generation,
image translation, face image editing, image quality improvement, general image
editing, anti-attack, voice signal processing and other fields. Through reading
this book, readers will thoroughly understand the principles of GAN, various
GAN model designs, and learn to apply GAN for most vision and voice tasks.
This book is suitable for the junior
researchers, students or industrial practitioners in related areas.
Pages
436 pages
Collection
n.c
Parution
2026-02-02
Marque
Springer
EAN papier
9789819694037
EAN PDF
9789819694044

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
29297 Ko
Prix
79,11 €
EAN EPUB
9789819694044

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
51354 Ko
Prix
79,11 €

Long Peng, an expert and senior author in the

field of deep learning. He is currently the CEO of Beijing YouSan Educational

Technology Co., Ltd.. He is the Most Valuable Professional of Alibaba Cloud and

HUAWEI Cloud, Publicity Chair in HDIS 2022. He has published four books alone

and one book with others in recent 5 years and is one of the leaders in book

creation in the field of deep learning and computer vision in China.

Xiaozhou Guo, China Electronics Technology Group Corporation No. 54 Research Institute.His main research directions include artificial intelligence and communication intelligence. He has co-authored 1 monograph in the past five years.

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