Diabetic retinopathy detection using deep learning techniques-Reference-Cited by-同舟云学术

Diabetic retinopathy detection using deep learning techniques

Published:2023 Issue: Volume: Page:
ISSN:0094-243X
Container-title:SUSTAINABLE DEVELOPMENTS IN MATERIALS SCIENCE, TECHNOLOGY AND ENGINEERING: Sustainable Development in Material Science of Today Is the Innovation of Tomorrow
language:
Short-container-title:

Author:

Rajendran Sowmia Kanakam,Mathew Dennise,Rajendiran Babu,Kandasamy Vijay

Publisher

AIP Publishing

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0152424

Reference17 articles.

1. N. Cheung, G. Tikellis, and J. J. Wang, ``Diabetic retinopathy,’’ Ophthalmology, vol. 114, no. 11, pp. 2098-2099, 2010.

2. R. Casanova, S. Saldana, E. Y. Chew, R. P. Danis, C. M. Greven, and W. T. Ambrosius, ``Application of random forests methods to diabetic retinopathy classi_cation analyses,’ ’PLoS One, vol. 9, no. 6, p. e98587, 2014.

3. G. Quellec, K. Charrière, Y. Boudi, B. Cochener, and M. Lamard, ``Deep image mining for diabetic Med. Image Anal., Vol. 39, pp. 178-193, Jul. 2017.

4. A. Ahmad, A. B. Mansoor, R. Mumtaz, M. Khan, and S. H. Mirza, ``Image processing and classi_cation in diabetic retinopathy: A review,’’ in Proc. Eur. Workshop Vis. Inf. Process., Dec. 2015, pp. 1-6.

5. H. F. Jaafar, A. K. Nandi, and W. Al-Nuaimy, `Automated detection and grading of hard exudates fromretinal fundus images,’’ in Proc. 19th Eur. Signal Process. Conf., 2011, pp. 66-70.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing Lung Disease Diagnosis through Meta Learning: A Framework Utilizing Few-Shot Learning Techniques;2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI);2024-05-09