A survey on recent developments in diabetic retinopathy detection through integration of deep learning
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/s11042-022-13837-5.pdf
Reference108 articles.
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3. Abràmoff MD, Lou Y, Erginay A, Clarida W, Amelon R, Folk JC, Niemeijer M (2016) Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning. Investig Ophthalmol Vis Sci 57(13):5200–5206
4. Achanta SDM, Karthikeyan T, Kanna RV (2021) Wearable sensor based acoustic gait analysis using phase transition-based optimization algorithm on IoT. Int J Speech Technol. https://doi.org/10.1007/s10772-021-09893-1
5. Adal KM, Van Etten PG, Martinez JP, Rouwen KW, Vermeer KA, van Vliet LJ (2017) An automated system for the detection and classification of retinal changes due to red lesions in longitudinal fundus images. IEEE Trans Biomed Eng 65(6):1382–1390
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