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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

Breaking down the face recognition problem

Let's break down the face recognition problem into smaller steps and subproblems. That way, we can better understand what's going on under the hood of a facial recognition system. A face recognition problem can be broken down into the following smaller subproblems:

  • Face detection: Detect and isolate faces in the image. In an image with multiple faces, we need to detect each of them separately. In this step, we should also crop the detected faces from the original input image, to identify them separately.
  • Face recognition: For each detected face in the image, we run it through a neural network to classify the subject. Note that we need to repeat this step for each detected face.

Intuitively, this process makes a lot of sense. If we think of how humans recognize faces, we see that it is very similar to the process that we described...

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