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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

Face Recognition

In this chapter, we will explore the challenges and the solutions related to the face recognition problem. Therefore, we are going to first present the face recognition problem nature and the similarity function as the general high-level solution. Then, we will introduce Siamese networks, which, together with the similarity function, constitute the fundamental techniques for solving face detection in an efficient manner. From there, we will proceed with two ways that have shown excellent results in training the convolutional neural network for face detection; the triplet loss function and binary classification. Finally, we will see how to use inception network like GoogLeNet and similar transfer learning and the triplet cost function to build the Java face recognition application. Additionally, we will be going through the code details and building a Java application...

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