A Traffic Sign Classification Method Using LiDAR Corrected Intensity and Geometric Feature-Reference-Cited by-同舟云学术

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A Traffic Sign Classification Method Using LiDAR Corrected Intensity and Geometric Feature

Published:2024-04-01 Issue:7 Volume:24 Page:11796-11804
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Li Xiaolu¹^ORCID,Yu Ruiqin²^ORCID,Bi Tengfei³^ORCID,Xu Lijun¹^ORCID

Affiliation:

1. School of Instrumentation and Optoelectronic Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China

2. School of Instrumentation and Optoelectronic Engineering, Shen Yuan Honors College, Beihang University, Beijing, China

3. School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China

Funder

National Natural Science Foundation of China

Science and Technology on Space Intelligent Control Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10487994/10436576.pdf?arnumber=10436576

Reference23 articles.

1. Autonomous Vehicles and Intelligent Automation: Applications, Challenges, and Opportunities

2. Towards Real-Time Traffic Sign Detection and Classification

3. Learning Automated Driving in Complex Intersection Scenarios Based on Camera Sensors: A Deep Reinforcement Learning Approach

4. Recent Advances in Traffic Sign Recognition: Approaches and Datasets

5. 3D CNN-Based Semantic Labeling Approach for Mobile Laser Scanning Data

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