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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

Image Retrieval

Deep learning can also be called representation learning because the features or representations in the model are learned during training. The visual features generated during the training process in the hidden layers can be used for computing a distance metric. These models learn how to detect edges, patterns, and so on at various layers, depending on the classification task. In this chapter, we will look at the following:

  • How to extract features from a model that was trained for classification
  • How to use TensorFlow Serving for faster inference in production systems
  • How to compute similarity between a query image and the set of targets using those features
  • Using the classification model for ranking
  • How to increase the speed of the retrieval system
  • Looking at the architecture of the system as a whole
  • Learning a compact descriptor when the target images are...
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