e20e9dd5-cb29-4814-b403-7a5dedb6fb1d beie director@blueeyesintelligence.org 10.35940/ijrte.B7175.0711222 10.38124/IJISRT20JUN711Jayshree Aher, Araadhya Sharma, Sashank Vemulapalli, Pragat Singh, and Meet Shah. "Diabetic Eye Disease Detection Using Machine Learning Techniques," Interna- tional Journal of Innovative Science and Research Technology (IJISRT), vol. 5, no. 6 pp. 752-755, 2020 [CrossRef]10.35940/ijeat.D7786.049420V. Sudha, K. Priyanka, T. Suvathi Kannathal, S. Monisha "Diabetic Retinopathy De- tection," International Journal of Engineering and Advanced Technology (IJEAT), vol. 9 , no. 4 pp. 1022-1026, 2020. [CrossRef]10.1109/ACCESS.2019.2903171X. Zeng, H. Chen, Y. Luo, and W. Ye, "Automated Diabetic Retinopathy Detection Based on Binocular Siamese-Like Convolutional Neural Network," IEEE Access, vol. 7, pp. 30744-30753, 2019. [CrossRef]10.1109/ACCESS.2019.2947484S. Qummar et al., "A Deep Learning Ensemble Approach for Diabetic Retinopathy Detection," in IEEE Access, vol. 7, pp. 150530-150539, 2019. [CrossRef]10.3390/sym11060749Qureshi, Imran, Jun Ma, and Qaisar Abbas. "Recent development on detection meth- ods for the diagnosis of diabetic retinopathy." Symmetry, vol. 11, no. 6 pp. 749, 2019. [CrossRef]10.35940/ijeat.E7835.088619Prabhjot Kaur, S. Chatterjee, and D. Singh. "Neural network technique for diabetic retinopathy detection." International Journal of Engineering and Advanced Technology (IJEAT), vol. 8, no. 6, pp. 440-445, 2019. [CrossRef]10.1167/tvst.8.6.4F. Li, Z. Liu, H. Chen, M. Jiang, X. Zhang, and Z. Wu, "Automatic Detection of Dia - betic Retinopathy in Retinal Fundus Photographs Based on Deep Learning Algorithm," Translational vision science & technology, vol. 8, no. 6, 2019. [CrossRef]10.1007/s00521-018-3443-zA. Issac, M. K. Dutta, and C. M. Travieso, "Automatic computer vision-based detec - tion and quantitative analysis of indicative parameters for grading of diabetic retinopathy," Neural Computing & Applications, vol. 32, no. 20, pp. 15687-15697, 2018 [CrossRef]S. Chavan, A. Deshmukh, V. Patil, S. Shivathanu, and S. Joshi, "Enhancement and Feature Extraction of Fundus Images," International Journal of Innovative Science and Research Technology, vol. 3, no. 4, pp. 628-632, 2018.Y. Kumaran and C. M. Patil, "A brief review of the detection of diabetic retinopathy in human eyes using pre-processing & segmentation techniques," International Journal of Recent Technology and Engineering, vol. 7, no. 4. pp. 310-320, 2018.10.1080/03091902.2017.1358772Al-Jarrah, M. A., & Shatnawi, H. "Non-proliferative diabetic retinopathy symptom detection and classification using neural networks," Journal of medical engineering & technology, vol. 41, no. 6 pp. 498-505, 2017 [CrossRef]10.1109/IranianMVIP.2017.8342333Karami, Narjes, and Hossein Rabbani. "A dictionary learning based method for de - tection of diabetic retinopathy in color fundus images." In 2017 10th Iranian Conference on Machine Vision and Image Processing (MVIP), pp. 119-122. IEEE, 2017. [CrossRef]10.1109/INTERCON.2017.8079692Carrera, Enrique V., Andrés González, and Ricardo Carrera. "Automated detection of diabetic retinopathy using SVM." In 2017 IEEE XXIV International Conference on Elec- tronics, Electrical Engineering and Computing (INTERCON), pp. 1-4. IEEE, 2017. [CrossRef]10.1109/MAMI.2017.8307893Shirbahadurkar, S. D., V. M. Mane, and D. V. Jadhav. "A modern screening approach for detection of diabetic retinopathy." In 2017 2nd International Conference on Man and Machine Interfacing (MAMI), pp. 1-6. IEEE, 2017. [CrossRef]10.1001/jama.2016.17216V. Gulshan et al., "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs," JAMA, vol. 316, no. 22, pp. 2402-2410, 2016. [CrossRef]10.5120/20667-2485Shveta, and Gurmeen Kaur. "Review on: detection of diabetic retinopathy using SVM and MDA." IJCA. Vol. 117. No. 20 pp. 1-3, 2015. [CrossRef]10.1109/iNIS.2015.30Bhatkar, Amol Prataprao, and G. U. Kharat. "Detection of diabetic retinopathy in reti- nal images using MLP classifier." In 2015 IEEE international symposium on nanoelec- tronic and information systems, pp. 331-335. IEEE, 2015. [CrossRef]10.1080/21681163.2015.1051187Dutta, Malay Kishore, M. Parthasarathi, Shaumik Ganguly, Shaunak Ganguly, and Kshitij Srivastava. "An efficient image processing based technique for comprehensive de- tection and grading of nonproliferative diabetic retinopathy from fundus images." Com- puter Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Vol. 5, no. 3 pp. 195-207, 2015. [CrossRef]10.1109/EUVIP.2014.7018362Ahmad, Arslan, Atif Bin Mansoor, Rafia Mumtaz, Mukaram Khan, and S. H. Mirza. "Image processing and classification in diabetic retinopathy: A review." In 2014 5th Euro- pean Workshop on Visual Information Processing (EUVIP), pp. 1-6. IEEE, 2014. [CrossRef]10.1016/S0140-6736(09)62124-3N. Cheung, P. Mitchell, and T. Y. Wong, "Diabetic retinopathy," The Lancet, vol. 376, no. 9735, pp. 124-136, 2010. [CrossRef]10.1243/09544119JEIM486Acharya, U. R., et al. "Computer-Based Detection of Diabetes Retinopathy Stages Using Digital Fundus Images." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, vol. 223, no. 5, pp. 545-553, 2009. [CrossRef]