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Hands-On Neural Network Programming with C#

You're reading from   Hands-On Neural Network Programming with C# Add powerful neural network capabilities to your C# enterprise applications

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Product type Paperback
Published in Sep 2018
Publisher Packt
ISBN-13 9781789612011
Length 328 pages
Edition 1st Edition
Languages
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Author (1):
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Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
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Table of Contents (16) Chapters Close

Preface 1. A Quick Refresher 2. Building Our First Neural Network Together FREE CHAPTER 3. Decision Trees and Random Forests 4. Face and Motion Detection 5. Training CNNs Using ConvNetSharp 6. Training Autoencoders Using RNNSharp 7. Replacing Back Propagation with PSO 8. Function Optimizations: How and Why 9. Finding Optimal Parameters 10. Object Detection with TensorFlowSharp 11. Time Series Prediction and LSTM Using CNTK 12. GRUs Compared to LSTMs, RNNs, and Feedforward networks 13. Activation Function Timings
14. Function Optimization Reference 15. Other Books You May Enjoy

Face and Motion Detection

Now it is time for us to get into a really neat application. We'll start off by using the open source package http://www.aforgenet.com/ to build a face and motion detection application. To do this, you'll need to have a camera installed in your system to see live streaming video. From there, we will use that camera to detect faces as well as motion. In this chapter, we are going to show two separate examples: one for facial detection, the other for motion detection. We'll show you exactly what goes on, and just how fast you can add these capabilities into your application.

In this chapter, we will cover such topics as:

  • Facial detection
  • Motion detection
  • How to use the local video-integrated camera
  • Image filtering/algorithms

Let's start out with facial detection. In our example, I'm going to use my friendly little French bulldog...

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