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Deep Learning for Computer Vision

You're reading from   Deep Learning for Computer Vision Expert techniques to train advanced neural networks using TensorFlow and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788295628
Length 310 pages
Edition 1st Edition
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Author (1):
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Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started 2. Image Classification FREE CHAPTER 3. Image Retrieval 4. Object Detection 5. Semantic Segmentation 6. Similarity Learning 7. Image Captioning 8. Generative Models 9. Video Classification 10. Deployment 11. Other Books You May Enjoy

Neural artistic style transfer


The first application we will implement is the neural artistic style transfer. Here, we will transfer the style of Van Gogh art onto an image. An image can be considered as a combination of style and content. The artistic style transfer technique transforms an image to look like a painting with a specific painting style. We will see how to code this idea up. The loss function will compare the generated image with the content of the photo and style of the painting. Hence, the optimization is carried out for the image pixel, rather than for the weights of the network. Two values are calculated by comparing the content of the photo with the generated image followed by the style of the painting and the generated image.

Content loss

Since pixels are not a good choice, we will use the CNN features of various layers, as they are a better representation of the content. The initial layers as seen in Chapter 3, Image Retrieval, have high-frequency such as edges, corners...

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