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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
Toc

Table of Contents (18) Chapters close

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
Implementing a Deep Learning Model Using Keras

In chapter, Chapter 2Deep Dive into Deep Neural Networks, we learned about deep learning in detail, which means we have a solid foundation in this area. We are also closer to implementing computer vision solutions for self-driving cars. In this chapter, we will learn about the deep learning API Keras. This will help us with the implementation of deep learning models. We will also examine a deep learning implementation using the Auto-Mpg dataset. We'll start by understanding what Keras is, and then implement our first deep learning model.

In this chapter, we will cover the following topics:

  • Starting work with Keras
  • Keras for deep learning 
  • Building your first deep learning model

Let's get started!

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