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Neural Networks with Keras Cookbook

You're reading from   Neural Networks with Keras Cookbook Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789346640
Length 568 pages
Edition 1st Edition
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Authors (2):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Srinivas Pradeep Srinivas Pradeep
Author Profile Icon Srinivas Pradeep
Srinivas Pradeep
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Toc

Table of Contents (18) Chapters Close

Preface 1. Building a Feedforward Neural Network 2. Building a Deep Feedforward Neural Network FREE CHAPTER 3. Applications of Deep Feedforward Neural Networks 4. Building a Deep Convolutional Neural Network 5. Transfer Learning 6. Detecting and Localizing Objects in Images 7. Image Analysis Applications in Self-Driving Cars 8. Image Generation 9. Encoding Inputs 10. Text Analysis Using Word Vectors 11. Building a Recurrent Neural Network 12. Applications of a Many-to-One Architecture RNN 13. Sequence-to-Sequence Learning 14. End-to-End Learning 15. Audio Analysis 16. Reinforcement Learning 17. Other Books You May Enjoy

Semantic segmentation of objects in an image

In the previous section, we learned about performing segmentation on top of an image where the image contained only one object. In this segmentation, we will learn about performing segmentation so that we are able to distinguish between multiple objects that are present in an image of a road.

Getting ready

The strategy that we'll adopt to perform semantic segmentation on top of images of a road is as follows:

  1. Gather a dataset that has the annotation of where the multiple objects within an image are located:
    • A sample of the semantic image looks as follows:
  1. Convert the output mask into a multi dimensional array where there are as many columns as the number of all possible...
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