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TensorFlow 2.0 Computer Vision Cookbook

You're reading from   TensorFlow 2.0 Computer Vision Cookbook Implement machine learning solutions to overcome various computer vision challenges

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781838829131
Length 542 pages
Edition 1st Edition
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Author (1):
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Jesús Martínez Jesús Martínez
Author Profile Icon Jesús Martínez
Jesús Martínez
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Table of Contents (14) Chapters Close

Preface 1. Chapter 1: Getting Started with TensorFlow 2.x for Computer Vision 2. Chapter 2: Performing Image Classification FREE CHAPTER 3. Chapter 3: Harnessing the Power of Pre-Trained Networks with Transfer Learning 4. Chapter 4: Enhancing and Styling Images with DeepDream, Neural Style Transfer, and Image Super-Resolution 5. Chapter 5: Reducing Noise with Autoencoders 6. Chapter 6: Generative Models and Adversarial Attacks 7. Chapter 7: Captioning Images with CNNs and RNNs 8. Chapter 8: Fine-Grained Understanding of Images through Segmentation 9. Chapter 9: Localizing Elements in Images with Object Detection 10. Chapter 10: Applying the Power of Deep Learning to Videos 11. Chapter 11: Streamlining Network Implementation with AutoML 12. Chapter 12: Boosting Performance 13. Other Books You May Enjoy

Technical requirements

As usual, you'll get the most out of these recipes if you can access a GPU, given that some of the examples in this chapter are quite resource-intensive. Also, if there are any preparatory steps you'll need to perform in order to complete a recipe, you'll find them in the Getting ready sections provided. As a last remark, the code for this chapter is available in the companion repository on GitHub: https://github.com/PacktPublishing/Tensorflow-2.0-Computer-Vision-Cookbook/tree/master/ch12.

Check out the following link to see the Code in Action video:

https://bit.ly/2Ko3H3K.

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