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Applied Deep Learning and Computer Vision for Self-Driving Cars

You're reading from  Applied Deep Learning and Computer Vision for Self-Driving Cars

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781838646301
Pages 332 pages
Edition 1st Edition
Languages
Authors (2):
Sumit Ranjan Sumit Ranjan
Profile icon Sumit Ranjan
Dr. S. Senthamilarasu Dr. S. Senthamilarasu
Profile icon Dr. S. Senthamilarasu
View More author details

Table of Contents (18) Chapters

Preface 1. Section 1: Deep Learning Foundation and SDC Basics
2. The Foundation of Self-Driving Cars 3. Dive Deep into Deep Neural Networks 4. Implementing a Deep Learning Model Using Keras 5. Section 2: Deep Learning and Computer Vision Techniques for SDC
6. Computer Vision for Self-Driving Cars 7. Finding Road Markings Using OpenCV 8. Improving the Image Classifier with CNN 9. Road Sign Detection Using Deep Learning 10. Section 3: Semantic Segmentation for Self-Driving Cars
11. The Principles and Foundations of Semantic Segmentation 12. Implementing Semantic Segmentation 13. Section 4: Advanced Implementations
14. Behavioral Cloning Using Deep Learning 15. Vehicle Detection Using OpenCV and Deep Learning 16. Next Steps 17. Other Books You May Enjoy

Building blocks of an image

In this section, we will learn the fundamentals of how to represent an image in a digital format and how to use images in a better way in the machine learning world for tasks such as image manipulation.

We will start by looking at how humans see color. Let's assume we have a yellow box. The brain can see the color yellow. The light waves that are observed by the human eye are translated into color by the visual cortex of the brain. When we look at a yellow box, the wavelengths of the reflected light determine what color we see. The light waves reflect off the yellow box and hit our eyes with a wavelength of 570 to 580 nanometers (the wavelength of yellow light).

In the next section, we will read about the digital representation of images. We are going to use the OpenCV library to process an image.

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