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- Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
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Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
Sumit Ranjan, Dr. S. Senthamilarasu
Ebook
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.
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.
- 1. The Foundation of Self-Driving Cars
- 2. Dive Deep into Deep Neural Networks
- 3. Implementing a Deep Learning Model using Keras
- 4. Computer Vision for Self-Driving Cars
- 5. Finding Road Markings using OpenCV
- 6. Improving the Image Classifier with CNN
- 7. Road Sign Detection using Deep Learning
- 8. The Principles and Foundations of Semantic Segmentation
- 9. Implementation of Semantic Segmentation
- 10. Behavior Cloning using Deep Learning
- 11. Vehicle Detection using OpenCV and Deep Learning
- 12. Next Steps
- Title: Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
- Author: Sumit Ranjan, Dr. S. Senthamilarasu
- Original title: Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
- ISBN: 9781838647025, 9781838647025
- Date of issue: 2020-08-14
- Format: Ebook
- Item ID: e_2af9
- Publisher: Packt Publishing