Microaneurysms detection using fundus images based on deep convolutional neural network enabled fractional hunter osprey optimization
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/s11042-023-17350-1.pdf
Reference33 articles.
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2. Kaushik H, Singh D, Kaur M, Alshazly H, Zaguia A, Hamam H (2021) Diabetic retinopathy diagnosis from fundus images using stacked generalization of deep models. IEEE Access 9:108276–108292
3. Zhou L, Zhao Y, Yang J, Yu Q, Xu X (2018) Deep multiple instance learning for automatic detection of diabetic retinopathy in retinal images. IET Image Proc 12(4):563–571
4. Abbas Q, Fondon I, Sarmiento A, Jiménez S, Alemany P (2017) Automatic recognition of severity level for diagnosis of diabetic retinopathy using deep visual features. Med Biol Eng Compu 55:1959–1974
5. Tan JH, Fujita H, Sivaprasad S, Bhandary SV, Rao AK, Chua KC, Acharya UR (2017) Automated segmentation of exudates, haemorrhages, microaneurysms using single convolutional neural network. Inf Sci 420:66–76
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