Grading of Diabetic Retinopathy Using Machine Learning Techniques
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-6631-6_44
Reference20 articles.
1. Acharya U, Kim C, Ng E, Tamura T (2009) Computer-based detection of diabetes retinopathy stages using digital fundus images. J Eng Med 223(5):545–553
2. Saranya P, Umamaheswari, Sivaram, Jain, Bagchi (2021) Classification of different stages of diabetic retinopathy using convolutional neural networks. In: 2nd International proceedings on computation, automation and knowledge management (ICCAKM). IEEE, Dubai, pp 59–64
3. Wang, Lu, Wang, Chen (2018) Diabetic retinopathy stage classification using convolutional neural networks. In: International proceedings on information reuse and integration (IRI). IEEE, USA, pp. 465–471
4. Anitha J, Priyadharshini M (2014) A region growing method of optic disc segmentation in retinal images. In: International proceedings on electronics and communication systems. IEEE, Coimbatore, pp 1–5
5. Dey, Roy, Das, Chaudhuri (2012) Optic cup to disc ratio measurement for glaucoma diagnosis using harris corner. In: 3rd International proceedings on computing, communication, and networking technologies. IEEE, Coimbatore, pp 1–5
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