Farhan Nabil, Mohd Noor and Wan Hasbullah, Mohd Isa and Anwar P. P., Abdul Majeed (2020) The diagnosis of diabetic retinopathy by means of transfer learning with conventional machine learning pipeline. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 2 (2). pp. 62-67. ISSN 2637-0883. (Published)
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Abstract
Diabetic Retinopathy is one of the common eye diseases due to the complication of diabetes mellitus. Cotton wool spots, rough exudates, haemorrhages and microaneurysms are the symptoms of the diabetic retinopathy due to the fluid leakage that is caused by the high blood glucose level disorder. Early treatment to prevent a permanent blindness is important as it could save the diabetic retinopathy vision. Hence, in this study, we proposed to employ an automated detection method to diagnose the diabetic retinopathy. The dataset was obtained from the Kaggle Database and been divided for training, testing and validation purposes. Furthermore, Transfer Learning models, namely VGG19 were employed to extract the features before being processed by Machine Learning classifiers which are SVM, kNN and RF to classify the diabetic retinopathy. VGG19-SVM pipeline produced the best accuracy in training, testing and validation processes, achieving 99, 99 and 96 percents respectively.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Diabetic retinopathy; Transfer learning; SVM; kNN; RF |
| Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 07 Apr 2022 02:04 |
| Last Modified: | 07 Apr 2022 02:04 |
| URI: | http://umpir.ump.edu.my/id/eprint/33640 |
| Download Statistic: | View Download Statistics |
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