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You're reading from Applied Deep Learning and Computer Vision for Self-Driving Cars Build autonomous vehicles using deep neural networks and behavior-cloning techniques

Product type Paperback

Published in Aug 2020

Publisher Packt

ISBN-13 9781838646301

Length 332 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Computer Vision

Authors (3):

Dr. S. Senthamilarasu

Balu Nair

Sumit Ranjan

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Table of Contents (18) Chapters

Preface

1. Section 1: Deep Learning Foundation and SDC Basics

2. The Foundation of Self-Driving Cars FREE CHAPTER

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

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To get the most out of this book

Let's look at what you need to get the most out the book:

Some Python programming experience and a basic understanding of deep learning are expected.
The execution of the code while reading the book will help you to get the most out of it.

Software/Hardware covered in the book	OS Requirements
Install Python 3.7 with latest Anaconda environment	Window, Linux or Mac minimum 8 GB RAM
Install deep learning libraries TensorFlow 2.0 and KERAS 2.3.4	Window, Linux or Mac minimum 8 GB RAM
Install image processing library OpenCV	Window, Linux or Mac minimum 8 GB RAM

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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Authors (2)

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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