Author:
Sasikala D.,Kowsalya T.,Padmaloshani P.,Ravindrakumar S.
Reference43 articles.
1. Classification of diabetic retinopathy with feature selection over deep features using nature-inspired wrapper methods;Canayaz;Appl. Soft Comput.,2022
2. Automatic severity classification of diabetic retinopathy based on densenet and convolutional block attention module;Farag;IEEE Access,2022
3. Performance evaluation of binary classification of diabetic retinopathy through deep learning techniques using texture feature;Adriman;Procedia Comput. Sci.,2021
4. Multi-level severity classification for diabetic retinopathy based on hybrid optimization enabled deep learning;Beevi;Biomed. Signal Process. Control,2023
5. Skouta, A., Elmoufidi, A., Jai-Andaloussi, S. and Ochetto, O., 2021. Automated binary classification of diabetic retinopathy by convolutional neural networks. InAdvances on Smart and Soft Computing: Proceedings of ICACIn 2020(pp. 177-187). Springer Singapore.
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