Book Image

Applied Deep Learning and Computer Vision for Self-Driving Cars

By : Sumit Ranjan, Dr. S. Senthamilarasu
Book Image

Applied Deep Learning and Computer Vision for Self-Driving Cars

By: Sumit Ranjan, Dr. S. Senthamilarasu

Overview of this book

Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries.
Table of Contents (18 chapters)
1
Section 1: Deep Learning Foundation and SDC Basics
5
Section 2: Deep Learning and Computer Vision Techniques for SDC
10
Section 3: Semantic Segmentation for Self-Driving Cars
13
Section 4: Advanced Implementations

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.