DFCAFNet: Dual-feature co-attentive fusion network for diabetic retinopathy grading-Reference-Cited by-同舟云学术

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DFCAFNet: Dual-feature co-attentive fusion network for diabetic retinopathy grading

Published:2024-10 Issue: Volume:96 Page:106564
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Madarapu Sandeep^ORCID,Ari Samit^ORCID,Mahapatra Kamalakanta^ORCID

Publisher

Elsevier BV

Reference60 articles.

1. Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images;Islam;Comput. Biol. Med.,2022

2. EDR-Net: Lightweight deep neural network architecture for detecting referable diabetic retinopathy;Aujih;IEEE Trans. Biomed. Circuits Syst.,2022

3. Deep residual transfer learning for automatic diagnosis and grading of diabetic retinopathy;Martinez-Murcia;Neurocomputing,2021

4. Diabetic retinopathy identification using parallel convolutional neural network based feature extractor and ELM classifier;Nahiduzzaman;Expert Syst. Appl.,2023

5. Deep learning for diabetic retinopathy assessments: a literature review;Skouta;Multimedia Tools Appl.,2023

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