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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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Generative Adversarial Networks and Deep Learning - Theory and Applications (Hardcover)
Loot Price: R4,352
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Generative Adversarial Networks and Deep Learning - Theory and Applications (Hardcover)
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This book explores how to use generative adversarial networks in a
variety of applications and emphasises their substantial
advancements over traditional generative models. This book's major
goal is to concentrate on cutting-edge research in deep learning
and generative adversarial networks, which includes creating new
tools and methods for processing text, images, and audio. A
Generative Adversarial Network (GAN) is a class of machine learning
framework and is the next emerging network in deep learning
applications. Generative Adversarial Networks(GANs) have the
feasibility to build improved models, as they can generate the
sample data as per application requirements. There are various
applications of GAN in science and technology, including computer
vision, security, multimedia and advertisements, image generation,
image translation,text-to-images synthesis, video synthesis,
generating high-resolution images, drug discovery, etc. Features:
Presents a comprehensive guide on how to use GAN for images and
videos. Includes case studies of Underwater Image Enhancement Using
Generative Adversarial Network, Intrusion detection using GAN
Highlights the inclusion of gaming effects using deep learning
methods Examines the significant technological advancements in GAN
and its real-world application. Discusses as GAN challenges and
optimal solutions The book addresses scientific aspects for a wider
audience such as junior and senior engineering, undergraduate and
postgraduate students, researchers, and anyone interested in the
trends development and opportunities in GAN and Deep Learning. The
material in the book can serve as a reference in libraries,
accreditation agencies, government agencies, and especially the
academic institution of higher education intending to launch or
reform their engineering curriculum
General
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