Generating a new reality : from autoencoders and adversarial networks to deepfakes / Micheal Lanham.
2021
QA76.624 .L36 2021
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Details
Title
Generating a new reality : from autoencoders and adversarial networks to deepfakes / Micheal Lanham.
Author
Lanham, Micheal, author.
ISBN
9781484270929 (electronic bk.)
1484270924 (electronic bk.)
9781484270912
1484270916
1484270924 (electronic bk.)
9781484270912
1484270916
Published
New York : Apress, [2021]
Copyright
©2021
Language
English
Description
1 online resource (xvii, 321 pages) : illustrations
Item Number
10.1007/978-1-4842-7092-9 doi
Call Number
QA76.624 .L36 2021
Dewey Decimal Classification
005.1/1
Summary
The emergence of artificial intelligence (AI) has brought us to the precipice of a new age where we struggle to understand what is real, from advanced CGI in movies to even faking the news. AI that was developed to understand our reality is now being used to create its own reality. In this book we look at the many AI techniques capable of generating new realities. We start with the basics of deep learning. Then we move on to autoencoders and generative adversarial networks (GANs). We explore variations of GAN to generate content. The book ends with an in-depth look at the most popular generator projects. By the end of this book you will understand the AI techniques used to generate different forms of content. You will be able to use these techniques for your own amusement or professional career to both impress and educate others around you and give you the ability to transform your own reality into something new. You will: Know the fundamentals of content generation from autoencoders to generative adversarial networks (GANs) Explore variations of GAN Understand the basics of other forms of content generation Use advanced projects such as Faceswap, deepfakes, DeOldify, and StyleGAN2.
Note
Includes index.
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Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Description based on print version record.
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Generating a new reality.
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Table of Contents
The basics of deep learning
Unleashing generative modeling
Exploring the latent space
GANs, GANs, and more GANs
Image to image content generation
Residual network GANs
Attention is all we need
Advanced generators
Deepfakes and face swapping
Cracking deepfakes
Appendix A: Running Google Colab locally
Appendix B: Opening a Notebook
Appendix C: Connecting Google Drive and saving.
Unleashing generative modeling
Exploring the latent space
GANs, GANs, and more GANs
Image to image content generation
Residual network GANs
Attention is all we need
Advanced generators
Deepfakes and face swapping
Cracking deepfakes
Appendix A: Running Google Colab locally
Appendix B: Opening a Notebook
Appendix C: Connecting Google Drive and saving.