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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

Who this book is for

This book is for undergraduate students and professionals who want to get started with computer vision and gain with a practical knowledge of implementing several of these algorithms. This book assumes that readers have a basic knowledge of Python and computer programs, they can write and run Python scripts (including scientific Python), and they can understand linear algebra and basic mathematics for programming.

This book will help readers in designing newer computer vision applications using image filtering, object detection, segmentation, tracking, and SLAM. Readers will understand the standard computer vision techniques used in the industry, as well as how to write their own code. Do the same as what with widely used libraries. They can use this to create their own applications across various domains, including image filtering, manipulating images, object detection, and advanced applications using deep learning. Readers will find a smooth transition from getting to know computer vision to using advanced techniques.

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