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Deep Learning for Computer Vision

You're reading from   Deep Learning for Computer Vision Expert techniques to train advanced neural networks using TensorFlow and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788295628
Length 310 pages
Edition 1st Edition
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Author (1):
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Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
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Table of Contents (12) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Image Classification 3. Image Retrieval 4. Object Detection 5. Semantic Segmentation 6. Similarity Learning 7. Image Captioning 8. Generative Models 9. Video Classification 10. Deployment 11. Other Books You May Enjoy

Summary

In this chapter, we have covered the basics of deep learning. The vocabulary introduced in this chapter will be used throughout this book, hence, you can refer back to this chapter often. The applications of computer vision are also shown with examples. Installations of all the software packages for various platforms for the development environment were also covered.

In the next chapter, we will discuss how to train classification models using both Keras and TensorFlow on a dataset. We will look at how to improve the accuracy using a bigger model and other techniques such as augmentation, and fine-tuning. Then, we will see several advanced models proposed by several people around the world, achieving the best accuracy in competitions. 

You have been reading a chapter from
Deep Learning for Computer Vision
Published in: Jan 2018
Publisher: Packt
ISBN-13: 9781788295628
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