Klasifikasi Penyakit Retina Menggunakan Transfer Learning - Green Ferry Mandias; George William Tangka; Ivanna Junamel Manoppo (Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma, 2026)
Retinal diseases such as Diabetic Retinopathy, glaucoma, and cataracts are major causes of global blindness that require early detection. However, manual screening faces challenges related to scalability and consistency, especially in resource-limited settings. This research aims to evaluate the comparative performance of six state-of-the-art Convolutional Neural Network (CNN) architectures to identify the most optimal model for the four-class retinal disease classification (cataract, diabetic retinopathy, glaucoma, and normal). The five models evaluated are EfficientNetB0, InceptionV3, MobileNetV2, VGG16, and VGG19. All models were trained using a transfer learning approach on the