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Open Access

Peer-reviewed

Research Article

Learning to recover weak signals: A two-stage graph-based framework for all-weather RGB-T object detection

Ruoyan Pei,

Roles Data curation, Methodology, Software, Writing – original draft

Affiliation School of Electronics and Information, Zhengzhou University of Aeronautics, Zhengzhou, China

https://orcid.org/0009-0006-3337-9063

⨯
Pengge Ma ,

Roles Supervision, Writing – review & editing

* E-mail: mapenge@163.com

Affiliation School of Electronics and Information, Zhengzhou University of Aeronautics, Zhengzhou, China
⨯
Jinwang Qian,

Roles Supervision, Writing – review & editing

Affiliation School of Electronics and Information, Zhengzhou University of Aeronautics, Zhengzhou, China
⨯
Hai Yang,

Roles Supervision, Writing – review & editing

Affiliation School of Electronics and Information, Zhengzhou University of Aeronautics, Zhengzhou, China
⨯
Junling Sun

Roles Supervision, Writing – review & editing

Affiliation School of Electronics and Information, Zhengzhou University of Aeronautics, Zhengzhou, China
⨯

Learning to recover weak signals: A two-stage graph-based framework for all-weather RGB-T object detection

Ruoyan Pei,
Pengge Ma,
Jinwang Qian,
Hai Yang,
Junling Sun

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Published: August 5, 2026
https://doi.org/10.1371/journal.pone.0354466

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