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Hands-On Java Deep Learning for Computer Vision

You're reading from   Hands-On Java Deep Learning for Computer Vision Implement machine learning and neural network methodologies to perform computer vision-related tasks

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789613964
Length 260 pages
Edition 1st Edition
Languages
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Author (1):
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Klevis Ramo Klevis Ramo
Author Profile Icon Klevis Ramo
Klevis Ramo
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Table of Contents (8) Chapters Close

Preface 1. Introduction to Computer Vision and Training Neural Networks 2. Convolutional Neural Network Architectures FREE CHAPTER 3. Transfer Learning and Deep CNN Architectures 4. Real-Time Object Detection 5. Creating Art with Neural Style Transfer 6. Face Recognition 7. Other Books You May Enjoy

Applying style cost function

In this section, we are going to see what is the style in terms of convolution layers, and then based on that intuition, we'll build the style cost function. In the end, we'll go through a slightly more formal definition of the style cost function.

How to capture the style

A part of the process is quite similar to what we have seen in the content cost function. So, we will still use convolution layers to capture image features and we will feed the neural network with a generated image, and then instead of the content image, we will use the style image here. And once we do that, we have the features captured for each of the layers.

Let's suppose that we pick up this layer as a feature...

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