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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

Convolutional Neural Network Architectures

In this chapter, we'll explore edge detection as one of the most fundamental and widely-used techniques in computer vision. Then, we'll look at edge detection in action, using a number of features and images, by building a Java application that detects edges on different images. As a next step, we'll detail how to use edge detection or convolution with colored RGB images so that we can capture even more features from images. We'll present them using several parameters, which will enable us to control the output of the convolution operation. Then, we'll look at a slightly different type of filter, the pooling layers, and one of the most frequently used: the max pooling layer. After that, we'll put all the pieces together for the purpose of building and training a convolution neural network. Finally, we&apos...

You have been reading a chapter from
Hands-On Java Deep Learning for Computer Vision
Published in: Feb 2019
Publisher: Packt
ISBN-13: 9781789613964
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