An improved deep learning approach for automated detection of multiclass eye diseases
Context: Early detection of ophthalmic diseases, such as drusen and glaucoma, can be facilitated by analyzing changes in the retinal microvascular structure. The implementation of algorithms based on convolutional neural networks (CNNs) has seen significant growth in the automation of disease identi...
Saved in:
| Main Authors: | Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Array |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590005625000797 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Air quality prediction based on factor analysis combined with Transformer and CNN-BILSTM-ATTENTION models
by: Shuyuan Liu, et al.
Published: (2025-06-01) -
Automated grading of oleaster fruit using deep learning
by: Aram Azadpour, et al.
Published: (2025-02-01) -
Single-level Discrete Two Dimensional Wavelet Transform Based Multiscale Deep Learning Framework for Two-Wheeler Helmet Detection
by: Amrutha Annadurai, et al.
Published: (2025-03-01) -
Automated detection of quiet eye durations in archery using electrooculography and comparative deep learning models
by: Fatma Söğüt, et al.
Published: (2025-08-01) -
A Comparative Study for Localization of Forgery Regions in Images
by: Mustafa Ozden, et al.
Published: (2025-01-01)