
Generative Adversarial Networks (GANs)
Adele Kuzmiakova(Editor)
Arcler Press
Published on 31. March 2026
Book
Hardback
240 pages
978-1-77956-417-7 (ISBN)
Description
Generative Adversarial Networks (GANs) are a class of machine learning models that have transformed the fields of artificial intelligence and creative technologies. By pitting two neural networks against each other, GANs generate highly realistic data, from images to text. This book explores the architecture, training methods, and diverse applications of GANs in healthcare, media, and research. With its in-depth analysis, it is essential for students, data scientists, and AI practitioners seeking to master this groundbreaking technology.
More details
Language
English
Place of publication
Canada
Target group
College/higher education
Product notice
Library binding
Dimensions
Height: 229 mm
Width: 152 mm
ISBN-13
978-1-77956-417-7 (9781779564177)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Adele Kuzmiakova is a machine learning engineer working at the intersection of machine learning, computer vision, and natural language processing. Adele attended Cornell University in New York, United States for her undergraduate studies. She studied engineering with a focus on applied math. Some of the deep learning problems Adele worked on include predicting air quality from public webcams, developing a real-time human movement tracking, using 3D computer vision to create 3D avatars from selfies in order to bring online clothes shopping closer to reality, and creating visual stories and photobooks from photos on mobile devices. She is also passionate about exchanging ideas and inspiring other people and acted as a workshop organizer at Women in Data Science conference in Geneva, Switzerland in 2022 and 2023.
Content
Chapter 1 Introduction to Generative Adversarial Networks (GANs)
Chapter 2 Architecture of Generative Adversarial Networks
Chapter 3 Types of Generative Adversarial Networks
Chapter 4 Training Generative Adversarial Networks (GANs)
Chapter 5 Security Issues in Generative Adversarial Networks
Chapter 6 Image Editing Using GANs
Chapter 7 Practical Applications of GANs
Chapter 8 Advanced Concepts in GANs
Chapter 2 Architecture of Generative Adversarial Networks
Chapter 3 Types of Generative Adversarial Networks
Chapter 4 Training Generative Adversarial Networks (GANs)
Chapter 5 Security Issues in Generative Adversarial Networks
Chapter 6 Image Editing Using GANs
Chapter 7 Practical Applications of GANs
Chapter 8 Advanced Concepts in GANs