Applied Deep Learning and Computer Vision for Self-Driving Cars

By Sumit Ranjan , Dr. S. Senthamilarasu
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  1. Section 1: Deep Learning Foundation and SDC Basics

About 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.

Publication date:
August 2020

Section 1: Deep Learning Foundation and SDC Basics

In this section, we will learn about the motivation behind becoming a self-driving car engineer, and the associated learning path, and we will get an overview of the different approaches and challenges found in the self-driving car field. It covers the foundations of deep learning, which are necessary, so that we can take a step toward the implementation of self-driving cars. This section provides a step-by-step explanation to enable you to understand deep neural network libraries such as Keras. It also covers the implementation of deep learning models from scratch by using Keras.

This section comprises the following chapters:

  • Chapter 1, The Foundation of Self-Driving Cars
  • Chapter 2Deep Dive into Deep Neural Networks
  • Chapter 3, Implementing a Deep Learning Model Using Keras

About the Authors

  • Sumit Ranjan

    Sumit Ranjan is a silver medalist in his Bachelor of Technology (Electronics and Telecommunication) degree. He is a passionate data scientist who has worked on solving business problems to build an unparalleled customer experience across domains such as, automobile, healthcare, semi-conductor, cloud-virtualization, and insurance. He is experienced in building applied machine learning, computer vision, and deep learning solutions, to meet real-world needs. He was awarded Autonomous Self-Driving Car Scholar by KPIT Technologies. He has also worked on multiple research projects at Mercedes Benz Research and Development. Apart from work, his hobbies are traveling and exploring new places, wildlife photography, and blogging.

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  • Dr. S. Senthamilarasu

    Dr. S. Senthamilarasu was born and raised in the Coimbatore, Tamil Nadu. He is a technologist, designer, speaker, storyteller, journal reviewer educator, and researcher. He loves to learn new technologies and solves real world problems in the IT industry. He has published various journals and research papers and has presented at various international conferences. His research areas include data mining, image processing, and neural network. He loves reading Tamil novels and involves himself in social activities. He has also received silver medals in international exhibitions for his research products for children with an autism disorder. He currently lives in Bangalore and is working closely with lead clients.

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