TL-4DRCF: A Two-Level 4-D Radar–Camera Fusion Method for Object Detection in Adverse Weather-Reference-Cited by-同舟云学术

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TL-4DRCF: A Two-Level 4-D Radar–Camera Fusion Method for Object Detection in Adverse Weather

Published:2024-05-15 Issue:10 Volume:24 Page:16408-16418
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Zhang Haoyi¹^ORCID,Wu Kai¹^ORCID,Chen Rongkang¹,Wu Zihao¹,Zhong Yong¹^ORCID,Li Weihua²^ORCID

Affiliation:

1. Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China

2. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, China

Funder

Development of the Marine Economy in Guangdong Province

Cooperative Scientific Research Project of the “Chunhui Program” of the Ministry of Education of China

Ministry of Education University-Industry Collaborative Education Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10530892/10491101.pdf?arnumber=10491101

Reference46 articles.

1. Multi-Object Detection and Tracking, Based on DNN, for Autonomous Vehicles: A Review

2. Deep Learning-Based Image 3-D Object Detection for Autonomous Driving: Review

3. Deep 3D Object Detection Networks Using LiDAR Data: A Review

4. Learn to Model and Filter Point Cloud Noise for a Near-Infrared ToF LiDAR in Adverse Weather

5. Low-Cost Hybrid Multisensor Fusion Method and Implementation for Production Intelligent Vehicles

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