Diabetic Retinopathy: Detection and Classification Using AlexNet, GoogleNet and ResNet50 Convolutional Neural Networks-Reference-Cited by-同舟云学术

Diabetic Retinopathy: Detection and Classification Using AlexNet, GoogleNet and ResNet50 Convolutional Neural Networks

Published:2022 Issue: Volume: Page:259-271
ISSN:1865-0929
Container-title:Smart Technologies, Systems and Applications
language:
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Author:

Caicho Jhonny^ORCID,Chuya-Sumba Cristina^ORCID,Jara Nicole^ORCID,Salum Graciela M.^ORCID,Tirado-Espín Andrés^ORCID,Villalba-Meneses Gandhi^ORCID,Alvarado-Cando Omar^ORCID,Cadena-Morejón Carolina^ORCID,Almeida-Galárraga Diego A.^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-99170-8_19

Reference47 articles.

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2. Alyoubi, W.L., Abulkhair, M.F., Shalash, W.M.: Diabetic retinopathy fundus image classification and lesions localization system using deep learning. Sensors. 21, 1–22 (2021). https://doi.org/10.3390/s21113704

3. Arcadu, F., et al.: Deep learning predicts OCT measures of diabetic macular thickening from color fundus photographs. Invest. Ophthalmol. Vis. Sci. 60, 852–857 (2019). https://doi.org/10.1167/iovs.18-25634

4. Communications in Computer and Information Science;A Pradhan,2020

5. Mookiah, M.R.K., et al.: Application of different imaging modalities for diagnosis of Diabetic Macular Edema: a review. Comput. Biol. Med. 66, 295–315 (2015). https://doi.org/10.1016/j.compbiomed.2015.09.012

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