Hybrid Deep Learning Models for Diabetic Retinopathy Classification-Reference-Cited by-同舟云学术

Hybrid Deep Learning Models for Diabetic Retinopathy Classification

Published:2022 Issue: Volume: Page:167-178
ISSN:2367-3370
Container-title:Proceedings of the 5th International Conference on Big Data and Internet of Things
language:
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Author:

Mikram Mounia^ORCID,Moujahdi Chouaib^ORCID,Rhanoui Maryem^ORCID,Meddad Majdouline^ORCID,Khallout Asmaa

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-07969-6_13

Reference36 articles.

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2. Acharya, U.R., Lim, C.M., Ng, E.Y.K., Chee, C., Tamura, T.: Computer-based detection of diabetes retinopathy stages using digital fundus images. Proc. Inst. Mech. Eng. Part H: J. Eng. Med. 223(5), 545–553 (2009)

3. Al-Rawi, M., Karajeh, H.: Genetic algorithm matched filter optimization for automated detection of blood vessels from digital retinal images. Comput. Methods Program. Biomed. 87(3), 248–253 (2007)

4. Alban, M., Gilligan, T.: Automated detection of diabetic retinopathy using fluorescein angiography photographs. Report of Standford Education (2016)

5. Asiri, N., Hussain, M., Al Adel, F., Alzaidi, N.: Deep learning based computer-aided diagnosis systems for diabetic retinopathy: a survey. Artif. Intell. Med. 99, 101701 (2019)

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