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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
Taschenbuch von Sumit Ranjan (u. a.)
Sprache: Englisch

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Beschreibung
Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV
Key Features

Build and train powerful neural network models to build an autonomous car

Implement computer vision, deep learning, and AI techniques to create automotive algorithms

Overcome the challenges faced while automating different aspects of driving using modern Python libraries and architectures

Book Description

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.

What you will learn

Implement deep neural network from scratch using the Keras library

Understand the importance of deep learning in self-driving cars

Get to grips with feature extraction techniques in image processing using the OpenCV library

Design a software pipeline that detects lane lines in videos

Implement a convolutional neural network (CNN) image classifier for traffic signal signs

Train and test neural networks for behavioral cloning by driving a car in a virtual simulator

Discover various state-of-the-art semantic segmentation and object detection architectures

Who this book is for

If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.
Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV
Key Features

Build and train powerful neural network models to build an autonomous car

Implement computer vision, deep learning, and AI techniques to create automotive algorithms

Overcome the challenges faced while automating different aspects of driving using modern Python libraries and architectures

Book Description

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.

What you will learn

Implement deep neural network from scratch using the Keras library

Understand the importance of deep learning in self-driving cars

Get to grips with feature extraction techniques in image processing using the OpenCV library

Design a software pipeline that detects lane lines in videos

Implement a convolutional neural network (CNN) image classifier for traffic signal signs

Train and test neural networks for behavioral cloning by driving a car in a virtual simulator

Discover various state-of-the-art semantic segmentation and object detection architectures

Who this book is for

If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.
Über den Autor
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.
Details
Erscheinungsjahr: 2020
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 332
ISBN-13: 9781838646301
ISBN-10: 1838646302
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Ranjan, Sumit
Senthamilarasu, S.
Hersteller: Packt Publishing
Maße: 235 x 191 x 19 mm
Von/Mit: Sumit Ranjan (u. a.)
Erscheinungsdatum: 14.08.2020
Gewicht: 0,622 kg
preigu-id: 118906196
Über den Autor
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.
Details
Erscheinungsjahr: 2020
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Seiten: 332
ISBN-13: 9781838646301
ISBN-10: 1838646302
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Ranjan, Sumit
Senthamilarasu, S.
Hersteller: Packt Publishing
Maße: 235 x 191 x 19 mm
Von/Mit: Sumit Ranjan (u. a.)
Erscheinungsdatum: 14.08.2020
Gewicht: 0,622 kg
preigu-id: 118906196
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