GD-STFA: Gradient Descent Sea Turtle Foraging Algorithm enabled Deep Q Network for Diabetic Retinopathy Detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17507-y.pdf
Reference27 articles.
1. Qiao L, Zhu Y, Zhou H (2020) Diabetic retinopathy detection using prognosis of microaneurysm and early diagnosis system for non-proliferative diabetic retinopathy based on deep learning algorithms. IEEE Access 8:104292–104302
2. Li X, Hu X, Yu L, Zhu L, Fu CW, Heng PA (2020) CANet: Cross-disease attention network for joint diabetic retinopathy and diabetic macular edema grading. IEEE Trans Med Imaging 39(5):1483–1493
3. Valarmathi R, Saravanan S (2021) Retracted article: Exudate characterization to diagnose diabetic retinopathy using generalized method. J Ambient Intell Humaniz Comput 12:3633–3645
4. Jemima Jebaseeli T, An C, Durai Deva, Dinesh Peter J (2018) Retinal blood vessel segmentation from depigmented diabetic retinopathy images. IETE J Res 67(2):263–280. https://doi.org/10.1080/03772063.2018.1535918
5. Álvaro SH, Rouco J, Novo J, Ortega M (2022) Multimodal image encoding pre-training for diabetic retinopathy grading. Comput Biol Med 143:105302. https://doi.org/10.1016/j.compbiomed.2022.105302
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