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Learn ARCore - Fundamentals of Google ARCore

You're reading from Learn ARCore - Fundamentals of Google ARCore Learn to build augmented reality apps for Android, Unity, and the web with Google ARCore 1.0

Product type Paperback

Published in Mar 2018

Publisher Packt

ISBN-13 9781788830409

Length 274 pages

Edition 1st Edition

Languages

JavaScript

Tools

Android

Concepts

Augmented Reality

Author (1):

Micheal Lanham

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started FREE CHAPTER

2. ARCore on Android

3. ARCore on Unity

4. ARCore on the Web

5. Real-World Motion Tracking

6. Understanding the Environment

7. Light Estimation

8. Recognizing the Environment

9. Blending Light for Architectural Design

10. Mixing in Mixed Reality

11. Performance Tips and Troubleshooting

12. Other Books You May Enjoy

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Training a neural network

As you may have already summarized, a neural network is essentially useless until it is trained. Before we get into training, we should talk some more on how a neuron is activated. Open up the Neuron class again and take a look at the CalculateValue function. This method calculates the output based on its internal set of weights and is described by the following:

Here:

Also, keep the following in mind:

n = total number of neurons connected as inputsI = signaled input to the Neuronclass

O = calculated output

S = the sigmoid function with a graph:

Sigmoid function

Sigmoid Function essentially distributes the weighted sum of values between 0 and 1 based on a curve (function) similar to the one shown in the preceding graph. We do this in order to evenly weigh the outputs of each of the neurons. Likewise, when we look to input data into a network, we also like to normalize the values between 0 and 1. If we didn't do this, one single neuron or input could bias our entire network...

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