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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 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

Content-based image retrieval

The technique of Content-based Image Retrieval (CBIR) takes a query image as the input and ranks images from a database of target images, producing the output. CBIR is an image to image search engine with a specific goal. A database of target images is required for retrieval. The target images with the minimum distance from the query image are returned. We can use the image directly for similarity, but the problems are as follows:

  • The image is of huge dimensions
  • There is a lot of redundancy in pixels
  • A pixel doesn't carry the semantic information

So, we train a model for object classification and use the features from the model for retrieval. Then we pass the query image and database of targets through the same model to get the features. The models can also be called encoders as they encode the information about the images...

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