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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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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

Kinds of machine learning techniques

In the previous section, we saw an introduction to machine learning and an example modeling of a digit image. Now, we will see the different styles of machine learning techniques.

Supervised learning

In supervised learning, we are given a dataset of both the inputs and required outputs for the model; our goal is to create a model that will take any previously unseen data and output values that are true to the actual as much as possible. There are two kinds of supervised learning.

Classification

This is the term for cases when the output...

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