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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

Gender classification of the person in image using the VGG19 architecture-based model

In the previous section, we learned about how VGG16 works. VGG19 is an improved version of VGG16, with a greater number of convolution and pooling operations.

Getting ready

The architecture of the VGG19 model is as follows:

Note that the preceding architecture has more layers, as well as more parameters.

Note that the 16 and 19 in the VGG16 and VGG19 architectures stand for the number of layers in each of these networks. Once we extract the 9 x 9 x 512 output after we pass each image through the VGG19 network, that output will be the input for our model.

Additionally, the process of creating input and output datasets and then building, compiling...

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