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Neural Networks with Keras Cookbook

You're reading from   Neural Networks with Keras Cookbook Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789346640
Length 568 pages
Edition 1st Edition
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Authors (2):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Srinivas Pradeep Srinivas Pradeep
Author Profile Icon Srinivas Pradeep
Srinivas Pradeep
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Toc

Table of Contents (18) Chapters Close

Preface 1. Building a Feedforward Neural Network 2. Building a Deep Feedforward Neural Network FREE CHAPTER 3. Applications of Deep Feedforward Neural Networks 4. Building a Deep Convolutional Neural Network 5. Transfer Learning 6. Detecting and Localizing Objects in Images 7. Image Analysis Applications in Self-Driving Cars 8. Image Generation 9. Encoding Inputs 10. Text Analysis Using Word Vectors 11. Building a Recurrent Neural Network 12. Applications of a Many-to-One Architecture RNN 13. Sequence-to-Sequence Learning 14. End-to-End Learning 15. Audio Analysis 16. Reinforcement Learning 17. Other Books You May Enjoy

CNNs to improve accuracy in the case of image translation

In the previous sections, we learned about the issue of translation in images and how a CNN works. In this section, we will leverage that knowledge to learn how a CNN works toward improving prediction accuracy when an image is translated.

Getting ready

The strategy that we will be adopting to build a CNN model is as follows:

  • Given that the input shape is 28 x 28 x 1, the filters shall be 3 x 3 x 1 in size:
    • Note that the size of filter can change, however the number of channels cannot change
  • Let's initialize 10 filters
  • We will perform pooling on top of the output obtained in the previous step of convolving 10 filters over the input image:
    • This would result...
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