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Hands-On Neural Networks with Keras

You're reading from   Hands-On Neural Networks with Keras Design and create neural networks using deep learning and artificial intelligence principles

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789536089
Length 462 pages
Edition 1st Edition
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Author (1):
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Niloy Purkait Niloy Purkait
Author Profile Icon Niloy Purkait
Niloy Purkait
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Fundamentals of Neural Networks FREE CHAPTER
2. Overview of Neural Networks 3. A Deeper Dive into Neural Networks 4. Signal Processing - Data Analysis with Neural Networks 5. Section 2: Advanced Neural Network Architectures
6. Convolutional Neural Networks 7. Recurrent Neural Networks 8. Long Short-Term Memory Networks 9. Reinforcement Learning with Deep Q-Networks 10. Section 3: Hybrid Model Architecture
11. Autoencoders 12. Generative Networks 13. Section 4: Road Ahead
14. Contemplating Present and Future Developments 15. Other Books You May Enjoy

Verifying the number of channels per layer

We saw that each layer has a depth that denoted the number of activation maps. These are also referred to as channels, where each channel contains an activation map, with a height and width of (n x n). Our first layer, for example, has 16 different maps of size 64 x 64. Similarly, the fourth layer has 16 activation maps of size 32 x 32. The eighth layer has 32 activation maps, each of size 16 x 16. Each of these activation maps was generated by a specific filter from its respective layer, and are passed forward to subsequent layers to encode higher-level features. This will concur with our smile detector model's architectural build, which we can always verify, as shown here:

Visualizing activation maps

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