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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
Provides a comprehensive guide about how to use machine vision for
Industry 4.0 applications like analysis of images for automated
inspections, object detection, object tracking etc. Includes case
studies of Robotics Internet of Things with its current and future
applications in Healthcare, Agriculture, Transportation, etc. It
highlights the inclusion of impaired people in industry, like
intelligent assistant that helps deaf-mute people to transmit
instructions and warnings in a manufacturing process. It examines
the significant technological advancements in machine vision for
industrial Internet of things and explores the commercial benefits
using the real world applications from healthcare to
transportation. Provides a conceptual framework of Machine vision
for the various Industrial applications. Addresses scientific
aspects for a wider audience such as senior and junior engineers,
undergraduate and post-graduate students, researchers, and anyone
else interested in the trends, development, and opportunities for
the Machine Vision for Industry 4.0 applications.
This book explores the significance, challenges and benefits of
digital twin technologies; it focuses in particular on various
architectures, applications and challenges in the implementation of
digital twins to Machine Learning and Internet of Things
capabilities. Through the analysis of smart city and smart
manufacturing case studies, the book explores the benefits of
digital technologies in the Industry 4.0 Era.
Deep learning, as a recent AI technique, has proven itself
efficient in solving many real-world problems. Deep learning
algorithms are efficient, high performing, and an effective
standard for solving these problems. In addition, with IoT, deep
learning is in many emerging and developing domains of computer
technology. Deep learning algorithms have brought a revolution in
computer vision applications by introducing an efficient solution
to several image processing-related problems that have long
remained unresolved or moderately solved. Various significant IoT
technologies in various industries, such as education, health,
transportation, and security, combine IoT with deep learning for
complex problem solving and the supported interaction between human
beings and their surroundings. The Handbook of Research on the
Impact of Deep Learning and IoT on Multi-Industry Applications
provides insights on how deep learning, together with IoT, impacts
various sectors such as healthcare, agriculture, cyber security,
and social media analysis applications. The chapters present
solutions to various real-world problems using these methods from
various researchers' points of view. While highlighting topics such
as medical diagnosis, power consumption, livestock management,
security, and social media analysis, this book is ideal for IT
specialists, technologists, security analysts, medical
practitioners, imaging specialists, diagnosticians, academicians,
researchers, industrial experts, scientists, and undergraduate and
postgraduate students who are working in the field of computer
engineering, electronics, and electrical engineering.
Deep learning, as a recent AI technique, has proven itself
efficient in solving many real-world problems. Deep learning
algorithms are efficient, high performing, and an effective
standard for solving these problems. In addition, with IoT, deep
learning is in many emerging and developing domains of computer
technology. Deep learning algorithms have brought a revolution in
computer vision applications by introducing an efficient solution
to several image processing-related problems that have long
remained unresolved or moderately solved. Various significant IoT
technologies in various industries, such as education, health,
transportation, and security, combine IoT with deep learning for
complex problem solving and the supported interaction between human
beings and their surroundings. Examining the Impact of Deep
Learning and IoT on Multi-Industry Applications provides insights
on how deep learning, together with IoT, impacts various sectors
such as healthcare, agriculture, cyber security, and social media
analysis applications. The chapters present solutions to various
real-world problems using these methods from various researchers'
points of view. While highlighting topics such as medical
diagnosis, power consumption, livestock management, security, and
social media analysis, this book is ideal for IT specialists,
technologists, security analysts, medical practitioners, imaging
specialists, diagnosticians, academicians, researchers, industrial
experts, scientists, and undergraduate and postgraduate students
who are working in the field of computer engineering, electronics,
and electrical engineering.
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Catan
(16)
R1,150
R887
Discovery Miles 8 870
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