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Open Access

Peer-reviewed

Research Article

Multi-scale error-driven dense residual network for image super-resolution reconstruction

Xueri Li,

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

Affiliation School of Computer Science, Guangdong University of Science and Technology, Dongguan, China
⨯
Lei Yang,

Roles Conceptualization, Data curation, Software, Visualization

Affiliation School of Computer Science, Guangdong University of Science and Technology, Dongguan, China
⨯
Shimin Liang,

Roles Conceptualization, Formal analysis, Validation, Visualization

Affiliation School of Computer Science, Guangdong University of Science and Technology, Dongguan, China
⨯
Jianfang Wu

Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

* E-mail: wujianfang314@gmail.com

Affiliations Faculty of Data Science, City University of Macau, Macau, China, College of Big Data and Internet, Shenzhen Technology University, Shenzhen, China

https://orcid.org/0000-0001-7213-5877

⨯

Multi-scale error-driven dense residual network for image super-resolution reconstruction

Xueri Li,
Lei Yang,
Shimin Liang,
Jianfang Wu

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Published: September 18, 2025
https://doi.org/10.1371/journal.pone.0330615

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