Autonomous Driving Perception Fundamentals and Applications /
Autonomous Driving Perception Fundamentals and Applications / [electronic resource] :
edited by Rui Fan, Sicen Guo, Mohammud Junaid Bocus.
- 1st ed. 2023.
- X, 387 p. 173 illus., 161 illus. in color. online resource.
- Advances in Computer Vision and Pattern Recognition, 2191-6594 .
- Advances in Computer Vision and Pattern Recognition, .
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.
9789819942879
10.1007/978-981-99-4287-9 doi
Robotics.
Machine learning.
Computer vision.
Robotics.
Machine Learning.
Computer Vision.
TJ210.2-211.495
629.892
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.
9789819942879
10.1007/978-981-99-4287-9 doi
Robotics.
Machine learning.
Computer vision.
Robotics.
Machine Learning.
Computer Vision.
TJ210.2-211.495
629.892