Traffic Accident Detection via Self-Supervised Consistency Learning in Driving Scenarios-Reference-Cited by-同舟云学术

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Traffic Accident Detection via Self-Supervised Consistency Learning in Driving Scenarios

Published:2022-07 Issue:7 Volume:23 Page:9601-9614
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Fang Jianwu¹^ORCID,Qiao Jiahuan²,Bai Jie²,Yu Hongkai³^ORCID,Xue Jianru¹^ORCID

Affiliation:

1. College of Transportation Engineering, Chang’an University, Xi’an, China

2. School of Electronic and Control Engineering, Chang’an University, Xi’an, China

3. Department of Electrical Engineering and Computer Science, Cleveland State University, Cleveland, OH, USA

Funder

National Natural Science Foundation of China

Natural Science Basic Research Plan in Shaanxi Province of China

Fundamental Research Funds for the Central Universities, CHD

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9826234/09733965.pdf?arnumber=9733965

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1. Real-time accident anticipation for autonomous driving through monocular depth-enhanced 3D modeling;Accident Analysis & Prevention;2024-11

2. Two-stream video-based deep learning model for crashes and near-crashes;Transportation Research Part C: Emerging Technologies;2024-09

3. Review of Accident Detection Methods Using Dashcam Videos for Autonomous Driving Vehicles;IEEE Transactions on Intelligent Transportation Systems;2024-08

4. Hierarchical Perception Enhancement for Different Levels of Autonomous Driving: A Review;IEEE Sensors Journal;2024-06-01

5. Anomaly Detection Methods in Autonomous Robotic Missions;Sensors;2024-02-19

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