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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 FREE CHAPTER 2. Convolutional Neural Network Architectures 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

Pooling layers

Let's see a slightly different type of layer, pooling layers, and, more specifically, we'll go in to the details of max pooling and average pooling.

Max pooling

Let's first explore how max pooling works. Similar to the convolution, we have the same parameters, the filter size is 2 x 2, the stride defines how big the step is, and we won't use any padding here:

Max pooling simply outputs the maximum of the selected values from the filter window, and, in this case, it would be nine.

It then moves the window on the right:

In this case, it moves two steps because of the stride, and outputs the maximum of the selected values, which is three.

It then moves down two steps and it outputs eight:

...
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