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Neural Network Projects with Python

You're reading from   Neural Network Projects with Python The ultimate guide to using Python to explore the true power of neural networks through six projects

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789138900
Length 308 pages
Edition 1st Edition
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Author (1):
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James Loy James Loy
Author Profile Icon James Loy
James Loy
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Table of Contents (10) Chapters Close

Preface 1. Machine Learning and Neural Networks 101 FREE CHAPTER 2. Predicting Diabetes with Multilayer Perceptrons 3. Predicting Taxi Fares with Deep Feedforward Networks 4. Cats Versus Dogs - Image Classification Using CNNs 5. Removing Noise from Images Using Autoencoders 6. Sentiment Analysis of Movie Reviews Using LSTM 7. Implementing a Facial Recognition System with Neural Networks 8. What's Next? 9. Other Books You May Enjoy

Summary

In this chapter, we created a face recognition system based on a Siamese neural network. The face recognition system uses a webcam to stream frames from a live video to a pre-trained Siamese neural network, and using a true image of the user, the system is able to authenticate the user in front of the webcam.

We first dissected the face recognition problem into smaller subproblems, and we saw how a face recognition system first performs a face detection step to isolate the face from the rest of the image, before the actual face recognition step. We saw how face detection is commonly done by the Viola-Jones algorithm, which uses Haar features to detect faces in real time. Face detection using Haar filters is implemented in Python via the OpenCV library, which allows us to perform face detection in just a few lines of code.

We then focused on face recognition, and we discussed...

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