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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

Image Classification

Image classification is the task of classifying a whole image as a single label. For example, an image classification task could label an image as a dog or a cat, given an image is either a dog or a cat. In this chapter, we will see how to use TensorFlow to build such an image classification model and also learn the techniques to improve the accuracy.

We will cover the following topics in this chapter:

  • Training the MNIST model in TensorFlow
  • Training the MNIST model in Keras
  • Other popular image testing datasets
  • The bigger deep learning models
  • Training a model for cats versus dogs
  • Developing real-world applications
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