Applied Deep Learning and Computer Vision for Self/Driving Cars

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Applied Deep Learning and Computer Vision for Self-Driving Cars

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Contributors

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Preface

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What this book covers

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Section 1: Deep Learning Foundation and SDC Basics

The Foundation of Self-Driving Cars

Introduction to SDCs

Challenges in current deployments

Levels of autonomy

Deep learning and computer vision approaches for SDCs

Summary

Dive Deep into Deep Neural Networks

Diving deep into neural networks

Understanding neurons and perceptrons

The workings of ANNs

Understanding activation functions

The cost function of neural networks

Optimizers

Understanding hyperparameters

TensorFlow versus Keras

Summary

Implementing a Deep Learning Model Using Keras

Starting work with Keras

Keras for deep learning

Building your first deep learning model

Summary

Section 2: Deep Learning and Computer Vision Techniques for SDC

Computer Vision for Self-Driving Cars

Introduction to computer vision

Building blocks of an image

Color space techniques

Introduction to convolution

Edge detection and gradient calculation

Image transformation

Summary

Finding Road Markings Using OpenCV

Finding road markings in an image

Detecting road markings in a video

Summary

Improving the Image Classifier with CNN

Images in computer format

Introducing CNNs

Introduction to handwritten digit recognition

Summary

Road Sign Detection Using Deep Learning

Dataset overview

Loading the data

Image exploration

Data preparation

Model training

Model accuracy

Summary

Section 3: Semantic Segmentation for Self-Driving Cars

The Principles and Foundations of Semantic Segmentation

Introduction to semantic segmentation

Understanding the semantic segmentation architecture

Overview of different semantic segmentation architectures

Summary

Implementing Semantic Segmentation

Semantic segmentation in images

Semantic segmentation in videos

Summary

Section 4: Advanced Implementations

Behavioral Cloning Using Deep Learning

Neural network for regression

Behavior cloning using deep learning

Summary

Vehicle Detection Using OpenCV and Deep Learning

What makes YOLO different?

The YOLO loss function

The YOLO architecture

Implementation of YOLO object detection

Summary

Next Steps

SDC sensors

Introduction to sensor fusion

Kalman filter

Summary

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