Abdo Salman, Abdulaziz and Ismail, Mohd Khairuddin and Anwar P. P., Abdul Majeed and Mohd Azraai, Mohd Razman (2020) The diagnosis of diabetic retinopathy by means of transfer learning and fine-tuned dense layer pipeline. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 2 (1). pp. 68-72. ISSN 2637-0883. (Published)
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Abstract
Diabetes is a global disease that occurs when the body is disabled pancreas to secrete insulin to convert the sugar to power in the blood. As a result, some tiny blood vessels on the part of the body, such as the eyes, are affected by high sugar and cause blocking blood flow in the vessels, which is called diabetic retinopathy. This disease may lead to permanent blindness due to the growth of new vessels in the back of the retina causing it to detach from the eyes. In 2016, 387 million people were diagnosed with Diabetic retinopathy, and the number is growing yearly, and the old detection approach becomes worse. Therefore, the purpose of this paper is to computerize the old method of detecting different classes of DR from 0-4 according to severity by given fundus images. The method is to construct a fine-tuned deep learning model based on transfer learning with dense layers. The used models here are InceptionV3, VGG16, and ResNet50 with a sharpening filter. Subsequently, InceptionV3 has achieved 94% as the highest accuracy among other models.
| Item Type: | Article |
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| Uncontrolled Keywords: | CNN; Transfer learning; Fine-tuning |
| Subjects: | R Medicine > RC Internal medicine T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 05 Apr 2022 02:55 |
| Last Modified: | 05 Apr 2022 02:55 |
| URI: | http://umpir.ump.edu.my/id/eprint/33619 |
| Download Statistic: | View Download Statistics |
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