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Fundus Image Super-Resolution Based on SRGAN with Efficient Channel Attention and Composite Degradation Modelin

2026-08-05

Abstract excerpt

<title>Abstract</title> <p>Conversional fundus images characterized by blurred vessel boundaries, weak local textures, and poor visibility of fine structures can compromise the extraction of clinically relevant features for fundus disease diagnosing. To address this issue, we developed a super‑resolution enhancement method based on a generative adversarial network (SRGAN) augmented with an efficient channel atten...

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Literature Corpus work: 56ab78f1-1216-5924-9e13-97fe84aec3a9
DOI: 10.21203/rs.3.rs-10581158/v1

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