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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

What are convolution network layers learning?

In this section, we will explore what the convolution layers are doing while learning. Understanding what activation layers are learning will not only help us to generate art, but will provide us with some useful insight that gives us greater opportunities for improvements.

First, we will see how to visualize the layers' knowledge, using the paper from Zeiler and Fergus 2013, which really does a great job in revealing what the layers are learning. Then we will look at a few examples from the same paper.

Let's look at the VGG-16 architecture, which we have studied previously in Chapter 3, Transfer Learning and Deep CNN Architectures, which has several convolution layers followed by fully connected layers and a softmax layer:

To train the model, we have to pick one of the layers, let's consider the second convolutional...

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