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Practical Convolutional Neural Networks

You're reading from   Practical Convolutional Neural Networks Implement advanced deep learning models using Python

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788392303
Length 218 pages
Edition 1st Edition
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Authors (3):
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Mohit Sewak Mohit Sewak
Author Profile Icon Mohit Sewak
Mohit Sewak
Md. Rezaul Karim Md. Rezaul Karim
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Md. Rezaul Karim
Pradeep Pujari Pradeep Pujari
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Pradeep Pujari
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Table of Contents (11) Chapters Close

Preface 1. Deep Neural Networks – Overview FREE CHAPTER 2. Introduction to Convolutional Neural Networks 3. Build Your First CNN and Performance Optimization 4. Popular CNN Model Architectures 5. Transfer Learning 6. Autoencoders for CNN 7. Object Detection and Instance Segmentation with CNN 8. GAN: Generating New Images with CNN 9. Attention Mechanism for CNN and Visual Models 10. Other Books You May Enjoy

Pix2pix - Image-to-Image translation GAN

This network uses a conditional generative adversarial network (cGAN) to learn mapping from the input and output of an image. Some of the examples that can be done from the original paper are as follows:

 Pix2pix examples of cGANs 

In the handbags example, the network learns how to color a black and white image. Here, the training dataset has the input image in black and white and the target image is the color version.

CycleGAN 

CycleGAN is also an image-to-image translator but without input/output pairs. For example, to generate photos from paintings, convert a horse image into a zebra image:

In a discriminator network, use of dropout is important. Otherwise,...
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