Regional feature fusion for on-road detection of objects using camera and 3D-LiDAR in high-speed autonomous vehicles

Autonomous vehicles require accurate, and fast decision-making perception systems to know the driving environment. The 2D object detection is critical in allowing the perception system to know the environment. However, 2D object detection lacks depth information, which are crucial for understanding...

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Vydáno v:	Soft computing (Berlin, Germany) Ročník 27; číslo 23; s. 18195 - 18213
Hlavní autoři:	Wu, Qingyu, Li, Xiaoxiao, Wang, Kang, Bilal, Hazrat
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023 Springer Nature B.V
Témata:	Application of Soft Computing Artificial Intelligence Artificial neural networks Automobile safety Autonomous vehicles Cameras Computational Intelligence Control Driving Engineering Feature extraction Feature maps Frames per second Human error Lasers Lidar Mathematical Logic and Foundations Mechatronics Methods Neural networks Object recognition Perception Planning Robotics Semantics Sensors Telematics Traffic Feature extraction CNN Autonomous vehicle 3D LIDAR Regional features Object detection
ISSN:	1432-7643, 1433-7479
On-line přístup:	Získat plný text
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