Optimising deep learning models for ophthalmological disorder classification

Optimising deep learning models for ophthalmological disorder classification

Abstract Fundus imaging, a technique for recording retinal structural components and anomalies, is essential for observing and identifying ophthalmological diseases. Disorders such as hypertension, glaucoma, and diabetic retinopathy are indicated by structural alterations in the optic disc, blood ve...

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Bibliographic Details
Main Authors: S. Vidivelli, P. Padmakumari, C. Parthiban, A. DharunBalaji, R. Manikandan, Amir H. Gandomi
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Transfer learning
DenseNet
ResNet
Lenet
Adam
Stochastic gradient descent
Online Access:https://doi.org/10.1038/s41598-024-75867-3
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