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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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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started 2. Image Classification FREE CHAPTER 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

Similarity Learning

In this chapter, we will learn about similarity learning and learn various loss functions used in similarity learning.  Similarity learning us useful when the dataset is small per class. We will understand different datasets available for face analysis and build a model for face recognition, landmark detection. We will cover the following topics in this chapter:

  • Different algorithms for similarity learning
  • Various loss functions used for similarity learning
  • A variety of scenarios in which such models can be used
  • The complete process of face recognition  
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