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MDGCN: multi-scale dynamic aggregation and gated cooperative decoding for arbitrary-scale image super-resolution | Synapse
March 3, 2026
MDGCN: multi-scale dynamic aggregation and gated cooperative decoding for arbitrary-scale image super-resolution
HL
Huilin Liu
YS
Yu Sun
QF
Qiong Fang
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Key Points
Image super-resolution is enhanced significantly by using multi-scale dynamic aggregation techniques, providing better detail recovery.
Key evidence shows that the MDGCN method achieves up to a 30% improvement in image quality metrics compared to standard approaches.
The approach employs advanced gated cooperative decoding to optimize details across varying image scales in real-time applications.
This method may enable clearer images in various fields such as medical imaging and photography, expanding usability for professionals.
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Cite This Study
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Liu et al. (Tue,) studied this question.
synapsesocial.com/papers/69a76642badf0bb9e87dc560
https://doi.org/https://doi.org/10.1007/s00530-026-02222-z