Generative Adversarial Networks and Deep Learning: Theory and Applications

This book explores how to use generative adversarial networks in a variety of applications and highlights their advancements over traditional generative models. It focuses on cutting-edge research in deep learning and GANs, including text, image, and audio processing. GANs have applications in computer vision, security, multimedia, and more. The book provides a comprehensive guide on using GAN for images and videos, with case studies and discussions of challenges and solutions. It is suitable for a wide audience, including students, researchers, and professionals interested in deep learning and GANs.

Format: Hardback
Length: 208 pages
Publication date: 10 April 2023
Publisher: Taylor & Francis Ltd

This captivating book delves into the realm of generative adversarial networks, exploring their diverse applications and highlighting their remarkable advancements over traditional generative models. Its primary objective is to delve into the forefront of cutting-edge research in deep learning and generative adversarial networks, encompassing the development of innovative tools and methodologies for processing text, images, and audio.

A Generative Adversarial Network (GAN) emerges as a groundbreaking machine learning framework, poised to revolutionize the field of deep learning applications. GANs possess the remarkable ability to generate sample data tailored to specific application requirements, thereby enhancing the model's performance and accuracy. Their applications span a wide range of scientific and technological domains, including computer vision, security, multimedia, advertising, image generation, image translation, text-to-image synthesis, video synthesis, generating high-resolution images, drug discovery, and more.

This comprehensive guide offers a thorough exploration of GANs, providing a comprehensive roadmap for their effective utilization in image and video applications. It includes captivating case studies, such as Underwater Image Enhancement Using Generative Adversarial Network and Intrusion Detection Using GAN, which vividly showcase the practical applications of GANs. Furthermore, the book highlights the integration of gaming effects using deep learning methods, expanding the horizons of GAN applications.

The book delves into the significant technological advancements made in GAN and their real-world applications, shedding light on their potential to transform various industries. It addresses the challenges associated with GANs and presents optimal solutions to overcome them. This book appeals to a diverse audience, including junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone with an interest in the latest trends and opportunities in GAN and deep learning.

As a valuable resource, this book will find a prominent place in libraries, accreditation agencies, government agencies, and academic institutions of higher education. Its comprehensive material serves as a valuable reference for scholars, researchers, and practitioners seeking to delve deeper into the world of generative adversarial networks and their profound impact on the field of deep learning.

Weight: 570g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032068107