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Generative Adversarial Networks Projects

You're reading from  Generative Adversarial Networks Projects

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781789136678
Pages 316 pages
Edition 1st Edition
Languages
Author (1):
Kailash Ahirwar Kailash Ahirwar
Profile icon Kailash Ahirwar

Table of Contents (11) Chapters

Preface 1. Introduction to Generative Adversarial Networks 2. 3D-GAN - Generating Shapes Using GANs 3. Face Aging Using Conditional GAN 4. Generating Anime Characters Using DCGANs 5. Using SRGANs to Generate Photo-Realistic Images 6. StackGAN - Text to Photo-Realistic Image Synthesis 7. CycleGAN - Turn Paintings into Photos 8. Conditional GAN - Image-to-Image Translation Using Conditional Adversarial Networks 9. Predicting the Future of GANs 10. Other Books You May Enjoy

Summary

In this chapter, we have introduced deep convolutional generative adversarial networks. We started with a basic introduction to DCGANs and then explored the architecture of the DCGAN network in depth. After that, we set up the project and installed the necessary dependencies. Then, we looked at the different steps required to download and prepare the dataset. We then prepared a Keras implementation of the network and trained it on our dataset. Once it was trained, we used it to generate new anime characters. We also explored different applications of DCGAN for real-world use cases.

In the next chapter, we will work on SRGANs for high-resolution image generation.

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