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Autonomous Driving Perception [electronic resource] : Fundamentals and Applications /

Contributor(s): Material type: TextTextSeries: Advances in Computer Vision and Pattern RecognitionPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2023Edition: 1st ed. 2023Description: X, 387 p. 173 illus., 161 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789819942879
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 629.892 23
LOC classification:
  • TJ210.2-211.495
Online resources:
Contents:
Chapter 1: Key Ingredients of Self-Driving Cars -- Chapter 2: Advanced Sensors for Next-Generation Autonomous Vehicles -- Chapter 3: Recent Advances in Multi-Camera and Camera-LIDAR Calibration -- Chapter 4: Deep Optical Flow for Autonomous Driving: A Review -- Chapter 5: Computer Stereo Vision for Autonomous Driving Perpection: From Explicit Programming to Deep Learning -- Chapter 6: Deep Monocular Depth Estimation for Autonomous Driving -- .
In: Springer Nature eBookSummary: Discover the captivating world of computer vision and deep learning for autonomous driving with our comprehensive and in-depth guide. Immerse yourself in an in-depth exploration of cutting-edge topics, carefully crafted to engage tertiary students and ignite the curiosity of researchers and professionals in the field. From fundamental principles to practical applications, this comprehensive guide offers a gentle introduction, expert evaluations of state-of-the-art methods, and inspiring research directions. With a broad range of topics covered, it is also an invaluable resource for university programs offering computer vision and deep learning courses. This book provides clear and simplified algorithm descriptions, making it easy for beginners to understand the complex concepts. We also include carefully selected problems and examples to help reinforce your learning. Don't miss out on this essential guide to computer vision and deep learning for autonomous driving.
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Chapter 1: Key Ingredients of Self-Driving Cars -- Chapter 2: Advanced Sensors for Next-Generation Autonomous Vehicles -- Chapter 3: Recent Advances in Multi-Camera and Camera-LIDAR Calibration -- Chapter 4: Deep Optical Flow for Autonomous Driving: A Review -- Chapter 5: Computer Stereo Vision for Autonomous Driving Perpection: From Explicit Programming to Deep Learning -- Chapter 6: Deep Monocular Depth Estimation for Autonomous Driving -- .

Discover the captivating world of computer vision and deep learning for autonomous driving with our comprehensive and in-depth guide. Immerse yourself in an in-depth exploration of cutting-edge topics, carefully crafted to engage tertiary students and ignite the curiosity of researchers and professionals in the field. From fundamental principles to practical applications, this comprehensive guide offers a gentle introduction, expert evaluations of state-of-the-art methods, and inspiring research directions. With a broad range of topics covered, it is also an invaluable resource for university programs offering computer vision and deep learning courses. This book provides clear and simplified algorithm descriptions, making it easy for beginners to understand the complex concepts. We also include carefully selected problems and examples to help reinforce your learning. Don't miss out on this essential guide to computer vision and deep learning for autonomous driving.

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