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Generating a new realityfrom autoenc...

Lanham, Micheal.

Generating a new realityfrom autoencoders and adversarial networks to deepfakes /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Generating a new realityby Micheal Lanham.
Reminder of title:	from autoencoders and adversarial networks to deepfakes /
Author:	Lanham, Micheal.
Published:	Berkeley, CA :Apress :2021.
Description:	xvii, 321 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Generative programming (Computer science)
Online resource:	https://doi.org/10.1007/978-1-4842-7092-9
ISBN:	9781484270929$q(electronic bk.)

Generating a new realityfrom autoencoders and adversarial networks to deepfakes /
Lanham, Micheal.

Generating a new realityfrom autoencoders and adversarial networks to deepfakes /[electronic resource] :by Micheal Lanham. - Berkeley, CA :Apress :2021. - xvii, 321 p. :ill., digital ;24 cm.

Chapter 1: The Basics of Deep Learning -- Chapter 2: Unleashing Generative Modeling -- Chapter 3: Exploring the Latent Space -- Chapter 4: GANs, GANs, and More GANs -- Chapter 5: Image to Image Generation with GANs -- Chapter 6: Residual Network GANs -- Chapter 7: Attention Is All We Need -- Chapter 8: Advanced Generators -- Chapter 9: Deepfakes and Faceswapping -- Chapter 10: Cracking Deepfakes -- Appendix A: Running Google Colab Locally -- Appendix B: Opening a Notebook -- Appendix C: Connecting Google Drive and Saving.

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.

ISBN: 9781484270929$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-7092-9doiSubjects--Topical Terms:

189324
Generative programming (Computer science)

LC Class. No.: QA76.624 / .L36 2021

Dewey Class. No.: 005.11

Generating a new realityfrom autoencoders and adversarial networks to deepfakes /
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505 0 $a Chapter 1: The Basics of Deep Learning -- Chapter 2: Unleashing Generative Modeling -- Chapter 3: Exploring the Latent Space -- Chapter 4: GANs, GANs, and More GANs -- Chapter 5: Image to Image Generation with GANs -- Chapter 6: Residual Network GANs -- Chapter 7: Attention Is All We Need -- Chapter 8: Advanced Generators -- Chapter 9: Deepfakes and Faceswapping -- Chapter 10: Cracking Deepfakes -- Appendix A: Running Google Colab Locally -- Appendix B: Opening a Notebook -- Appendix C: Connecting Google Drive and Saving.
520 $a 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.
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