Titlebook: Autonomous Driving Perception; Fundamentals and App Rui Fan,Sicen Guo,Mohammud Junaid Bocus Book 2023 The Editor(s) (if applicable) and The

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Liang Zhao,Lingfei Wu,Peng Cui,Jian Peies a large field of view (FoV). Because of this special feature, the fish-eye camera has abundant applications in environmental perception and autonomous driving. However, many challenges still exist in the practical application of fish-eye cameras. In this chapter, typical fish-eye datasets, includ

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完成才能戰(zhàn)勝

Background and Traditional Approaches,s belonging to the same category using artificial intelligence. This is an important step from image processing to image analysis and has numerous applications in areas such as automatic driving, image enhancement, and 3D map reconstruction. With the emergence of deep learning, several sophisticated

Aphorism

FLEET

Multi-Relational Data and Knowledge Graphsindividual vehicles results in the bottleneck of improvement of the 3D detection performance. To break through the limits of individual detection, collaborative 3D object detection has been proposed which enables agents to share information to perceive the environments beyond line-of-sight and field

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Background and Traditional Approaches,ress in solving the probabilistic SLAM problem by presenting various theoretical frameworks, efficient solvers, and complete systems. As the development of autonomous robots (i.e., self-driving cars, legged robots) continues, SLAM systems have become increasingly popular for large-scale real-world a

TEM

Traditional Graph Generation ApproachesM) systems. However, retrieving ground truth, estimating calibration parameters and annotating useful labels all require cumbersome human labor. Moreover, there are lots of object instances in the environments while traditional mapping modules can only estimate 3D information of isolated sparse or s

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