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Advanced Deep Learning with Keras

You're reading from  Advanced Deep Learning with Keras

Product type Book
Published in Oct 2018
Publisher Packt
ISBN-13 9781788629416
Pages 368 pages
Edition 1st Edition
Languages
Author (1):
Rowel Atienza Rowel Atienza
Profile icon Rowel Atienza

Table of Contents (13) Chapters

Preface 1. Introducing Advanced Deep Learning with Keras 2. Deep Neural Networks 3. Autoencoders 4. Generative Adversarial Networks (GANs) 5. Improved GANs 6. Disentangled Representation GANs 7. Cross-Domain GANs 8. Variational Autoencoders (VAEs) 9. Deep Reinforcement Learning 10. Policy Gradient Methods Other Books You May Enjoy Index

Principles of GANs


As shown in Figure 4.1.1 a GAN is analogous to a counterfeiter (generator) - police (discriminator) scenario. At the academy, the police are taught how to determine if a dollar bill is either genuine or fake. Samples of real dollar bills from the bank and fake money from the counterfeiter are used to train the police. However, from time to time, the counterfeiter will attempt to pretend that he printed real dollar bills. Initially, the police will not be fooled and will tell the counterfeiter why the money is fake. Taking into consideration this feedback, the counterfeiter hones his skills again and attempts to produce new fake dollar bills. As expected the police will be able to both spot the money as fake and justify why the dollar bills are fake.

Figure 4.1.1: The generator and discriminator of GANs are analogous to the counterfeiter and the police. The goal of the counterfeiter is to fool the police into believing that the dollar bill is real.

This scenario continues...

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