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Practical Convolutional Neural Networks

You're reading from   Practical Convolutional Neural Networks Implement advanced deep learning models using Python

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788392303
Length 218 pages
Edition 1st Edition
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Authors (3):
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Mohit Sewak Mohit Sewak
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Mohit Sewak
Md. Rezaul Karim Md. Rezaul Karim
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Md. Rezaul Karim
Pradeep Pujari Pradeep Pujari
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Pradeep Pujari
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Table of Contents (11) Chapters Close

Preface 1. Deep Neural Networks – Overview 2. Introduction to Convolutional Neural Networks FREE CHAPTER 3. Build Your First CNN and Performance Optimization 4. Popular CNN Model Architectures 5. Transfer Learning 6. Autoencoders for CNN 7. Object Detection and Instance Segmentation with CNN 8. GAN: Generating New Images with CNN 9. Attention Mechanism for CNN and Visual Models 10. Other Books You May Enjoy

Summary

We began this chapter by briefly looking into the history of CNNs. We introduced you to the implementation of visualizing images. 

We studied image classification with the help of a practical example, using all the principles we learned about in the chapter. Finally, we learned how image augmentation helps us avoid overfitting and studied the various other features provided by image augmentation.

In the next chapter, we will learn how to build a simple image classifier CNN model from scratch.

You have been reading a chapter from
Practical Convolutional Neural Networks
Published in: Feb 2018
Publisher: Packt
ISBN-13: 9781788392303
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