Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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1 Online-Ressource.
- Language
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Englisch
- Bibliographic citation
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Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas ; volume:17 ; number:1 ; day:29 ; month:5 ; year:2024 ; pages:1-20 ; date:12.2024
International journal of computational intelligence systems ; 17, Heft 1 (29.5.2024), 1-20, 12.2024
- Creator
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Jabbar, Ayesha
Naseem, Shahid
Li, Jianqiang
Mahmood, Tariq
Jabbar, Muhammad Kashif
Rehman, Amjad
Saba, Tanzila
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s44196-024-00520-w
- URN
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urn:nbn:de:101:1-2409110925581.745832549379
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:33 AM CEST
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Associated
- Jabbar, Ayesha
- Naseem, Shahid
- Li, Jianqiang
- Mahmood, Tariq
- Jabbar, Muhammad Kashif
- Rehman, Amjad
- Saba, Tanzila
- SpringerLink (Online service)
Other Objects (12)
Correction: Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas
Diagnosing Hypertensive Retinopathy through Retinal Images
Differential distribution of manifest lesions in diabetic retinopathy by fundus fluorescein angiography and fundus photography
Microglia in retinal angiogenesis and diabetic retinopathy
Retinal Capillary Nonperfusion in Preclinical Diabetic Retinopathy
A fundus image dataset for intelligent retinopathy of prematurity system
Deep learning-based hemorrhage detection for diabetic retinopathy screening
Comparison of widefield swept-source optical coherence tomographic angiography and fluorescein fundus angiography for detection of retinal neovascularization with diabetic retinopathy
Digital innovations for retinal care in diabetic retinopathy
Dual wavelength retinal vessel oximetry – influence of fundus pigmentation
Deep Learning Based Quality Prediction of Retinal Fundus Images
Automatic detection of microaneurysms in RGB retinal fundus images
Correction: Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas
Diagnosing Hypertensive Retinopathy through Retinal Images
Differential distribution of manifest lesions in diabetic retinopathy by fundus fluorescein angiography and fundus photography
Microglia in retinal angiogenesis and diabetic retinopathy
Retinal Capillary Nonperfusion in Preclinical Diabetic Retinopathy
A fundus image dataset for intelligent retinopathy of prematurity system
Deep learning-based hemorrhage detection for diabetic retinopathy screening
Comparison of widefield swept-source optical coherence tomographic angiography and fluorescein fundus angiography for detection of retinal neovascularization with diabetic retinopathy
Digital innovations for retinal care in diabetic retinopathy
Dual wavelength retinal vessel oximetry – influence of fundus pigmentation
Deep Learning Based Quality Prediction of Retinal Fundus Images
Automatic detection of microaneurysms in RGB retinal fundus images
Correction: Deep Transfer Learning-Based Automated Diabetic Retinopathy Detection Using Retinal Fundus Images in Remote Areas
Diagnosing Hypertensive Retinopathy through Retinal Images
Differential distribution of manifest lesions in diabetic retinopathy by fundus fluorescein angiography and fundus photography
Microglia in retinal angiogenesis and diabetic retinopathy
Retinal Capillary Nonperfusion in Preclinical Diabetic Retinopathy
A fundus image dataset for intelligent retinopathy of prematurity system
Deep learning-based hemorrhage detection for diabetic retinopathy screening
Comparison of widefield swept-source optical coherence tomographic angiography and fluorescein fundus angiography for detection of retinal neovascularization with diabetic retinopathy
Digital innovations for retinal care in diabetic retinopathy
Dual wavelength retinal vessel oximetry – influence of fundus pigmentation
Deep Learning Based Quality Prediction of Retinal Fundus Images