Improved diabetic retinopathy severity classification using squeeze-and-excitation and sparse light weight multi-level attention u-net with transfer learning from xception
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00592-024-02341-x.pdf
Reference32 articles.
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3. Qummar S, Khan FG, Shah S et al. (2019) A deep learning ensemble approach for diabetic retinopathy detection. IEEE Access 7:150530–150539
4. Kang Q, Yang C (2020) Oxidative stress and diabetic retinopathy: Molecular mechanisms, pathogenetic role and therapeutic implications. Redox Biol 37:101799
5. Atwany MZ, Sahyoun AH, Yaqub M (2022) Deep learning techniques for diabetic retinopathy classification: a survey. IEEE Access 10:28642–28655
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