A Parallel Teacher for Synthetic-to-Real Domain Adaptation of Traffic Object Detection-Reference-Cited by-同舟云学术

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A Parallel Teacher for Synthetic-to-Real Domain Adaptation of Traffic Object Detection

Published:2022-09 Issue:3 Volume:7 Page:441-455
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Wang Jiangong¹^ORCID,Shen Tianyu²^ORCID,Tian Yonglin¹^ORCID,Wang Yutong¹^ORCID,Gou Chao³^ORCID,Wang Xiao¹^ORCID,Yao Fei⁴^ORCID,Sun Changyin⁵

Affiliation:

1. State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. School of Artificial Intelligence, Beijing Normal University, Beijing, China

3. School of Intelligent Systems Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China

4. North Automatic Control Technology Institute, Taiyuan, China

5. School of Artificial Intelligence, Anhui University, Hefei, China

Funder

Key-Area Research and Development Program of Guangdong Province

National Natural Science Foundation of China

Key Research and Development Program 2020 of Guangzhou

Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/9927386/09854126.pdf?arnumber=9854126

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2. GHAFNet: Global-context hierarchical attention fusion method for traffic object detection;Multimedia Tools and Applications;2024-02-05

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