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Hands-On Vision and Behavior for Self-Driving Cars

You're reading from   Hands-On Vision and Behavior for Self-Driving Cars Explore visual perception, lane detection, and object classification with Python 3 and OpenCV 4

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Product type Paperback
Published in Oct 2020
Publisher Packt
ISBN-13 9781800203587
Length 374 pages
Edition 1st Edition
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Authors (2):
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Krishtof Korda Krishtof Korda
Author Profile Icon Krishtof Korda
Krishtof Korda
Luca Venturi Luca Venturi
Author Profile Icon Luca Venturi
Luca Venturi
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Table of Contents (17) Chapters Close

Preface 1. Section 1: OpenCV and Sensors and Signals
2. Chapter 1: OpenCV Basics and Camera Calibration FREE CHAPTER 3. Chapter 2: Understanding and Working with Signals 4. Chapter 3: Lane Detection 5. Section 2: Improving How the Self-Driving Car Works with Deep Learning and Neural Networks
6. Chapter 4: Deep Learning with Neural Networks 7. Chapter 5: Deep Learning Workflow 8. Chapter 6: Improving Your Neural Network 9. Chapter 7: Detecting Pedestrians and Traffic Lights 10. Chapter 8: Behavioral Cloning 11. Chapter 9: Semantic Segmentation 12. Section 3: Mapping and Controls
13. Chapter 10: Steering, Throttle, and Brake Control 14. Chapter 11: Mapping Our Environments 15. Assessments 16. Other Books You May Enjoy

Chapter 7: Detecting Pedestrians and Traffic Lights

Congratulations on covering deep learning and progressing to this new section! Now that you know the basics of how to build and tune neural networks, it is time to move toward more advanced topics.

If you remember, in Chapter 1, OpenCV Basics and Camera Calibration, we already detected pedestrians using OpenCV. In this chapter, we will learn how to detect objects using a very powerful neural network called Single Shot MultiBox Detector (SSD), and we will use it to detect not only pedestrians but also vehicles and traffic lights. In addition, we will train a neural network to detect the color of the traffic lights using transfer learning, a powerful technique that can help you achieve good results using a relatively small dataset.

In this chapter, we will cover the following topics:

  • Detecting pedestrians, vehicles, and traffic lights
  • Collecting images with CARLA
  • Object detection with Single Shot MultiBox Detector...
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