You're reading from Advanced Deep Learning with Python

Product typeBook

Published inDec 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789956177

Edition1st Edition

Languages

Python

Tools

PyTorch TensorFlow

Concepts

Deep Learning

Author (1)

Ivan Vasilev

Introducing artistic style transfer

In this final section, we'll discuss artistic style transfer. Similar to one of the applications of CycleGAN, it allows us to use the style (or texture) of one image to reproduce the semantic content of another. Although it can be implemented with different algorithms, the most popular way was introduced in 2015 in the A Neural Algorithm of Artistic Style paper (https://arxiv.org/abs/1508.06576). It's also known as neural style transfer and it uses (you guessed it!) CNNs. The basic algorithm has been improved and tweaked over the past few years, but in this section we'll explore its original form as this will give us a good foundation for understanding the latest versions.

The algorithm takes two images as input:

The content image (C) we would like to redraw
The style image (I) whose style (texture) we'll use to redraw C...

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Advanced Deep Learning with Python

Published in: Dec 2019Publisher: PacktISBN-13: 9781789956177

Author (1)

Ivan Vasilev

Ivan Vasilev started working on the first open source Java deep learning library with GPU support in 2013. The library was acquired by a German company, with whom he continued its development. He has also worked as a machine learning engineer and researcher in medical image classification and segmentation with deep neural networks. Since 2017, he has focused on financial machine learning. He co-founded an algorithmic trading company, where he's the lead engineer. He holds an MSc in artificial intelligence from Sofia University St. Kliment Ohridski and has written two previous books on the same topic.
Read more about Ivan Vasilev

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Python Deep Learning

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