Applied Deep Learning and Computer Vision for Self-Driving Cars: Build autonomous vehicles using deep neural networks and behavior-cloning techniques

by Sumit Ranjan, Dr. S. Senthamilarasu

Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV

Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook DescriptionThanks 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.

What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is forIf you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.

Table of ContentsThe Foundation of Self-Driving CarsDive Deep into Deep Neural NetworksImplementing a Deep Learning Model using KerasComputer Vision for Self-Driving CarsFinding Road Markings using OpenCVImproving the Image Classifier with CNNRoad Sign Detection using Deep LearningThe Principles and Foundations of Semantic SegmentationImplementation of Semantic SegmentationBehavior Cloning using Deep LearningVehicle Detection using OpenCV and Deep Learning

334 pages, Kindle Edition

Published August 14, 2020

Reviews

[Moran Danieli-Cohen]

I found 'Applied Deep Learning and Computer Vision for Self-Driving Cars' to be a practical and example-driven book. The author does a good job of demonstrating how to use deep neural networks and behavior-cloning techniques to build autonomous vehicles.

However, I would not recommend this book for beginners as the technical details are not covered in-depth. This book is better suited for professionals who already have a solid understanding of these technologies.

Overall, I found the book to be informative and useful for those looking to apply deep learning and computer vision applications in differnet fields.

[Medhat ullah · Rating 5 out of 5]

read it probably for my "self-driving cars engineering" - fascinating Read