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Practical Computer Vision

You're reading from   Practical Computer Vision Extract insightful information from images using TensorFlow, Keras, and OpenCV

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788297684
Length 234 pages
Edition 1st Edition
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Author (1):
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Abhinav Dadhich Abhinav Dadhich
Author Profile Icon Abhinav Dadhich
Abhinav Dadhich
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Toc

Table of Contents (12) Chapters Close

Preface 1. A Fast Introduction to Computer Vision FREE CHAPTER 2. Libraries, Development Platform, and Datasets 3. Image Filtering and Transformations in OpenCV 4. What is a Feature? 5. Convolutional Neural Networks 6. Feature-Based Object Detection 7. Segmentation and Tracking 8. 3D Computer Vision 9. Mathematics for Computer Vision 10. Machine Learning for Computer Vision 11. Other Books You May Enjoy

Useful tools

In this section, we will see some of the tools that are used while creating machine learning models. Here, we will be using the scikit-learn package, but these are available in many other libraries too. The overall functioning and the purpose remain the same.

Preprocessing

Preprocessing the input as well as target labels in settings such as classification or regression is as important as the model itself. Some of the techniques used are explained as follows.

Normalization

For the ease of the model to learn proper parameters through a training set, it is highly...

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