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HandsOn Vision and Behavior for SelfDriving Cars: Explore visual perception, lane detection, and object classification with Py,Used
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A practical guide to learning visual perception for selfdriving cars for computer vision and autonomous system engineersKey Features Explore the building blocks of the visual perception system in selfdriving cars Identify objects and lanes to define the boundary of driving surfaces using opensource tools like OpenCV and Python Improve the object detection and classification capabilities of systems with the help of neural networksBook DescriptionThe visual perception capabilities of a selfdriving car are powered by computer vision. The work relating to selfdriving cars can be broadly classified into three components robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field.You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real selfdriving car is a huge crossfunctional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You'll even be able to tackle core challenges in selfdriving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller.By the end of this book, you'll be equipped with the skills you need to write code for a selfdriving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers.What You Will Learn Understand how to perform camera calibration Become wellversed with how lane detection works in selfdriving cars using OpenCV Explore behavioral cloning by selfdriving in a videogame simulator Get to grips with using lidars Discover how to configure the controls for autonomous vehicles Use object detection and semantic segmentation to locate lanes, cars, and pedestrians Write a PID controller to control a selfdriving car running in a simulatorWho this book is forThis book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.