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EfficientNetV2 Based Ensemble Model for Quality Estimation of Diabetic Retinopathy Images from DeepD...

EfficientNetV2 Based Ensemble Model for Quality Estimation of Diabetic Retinopathy Images from DeepD...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0f0e066b789e4581871ae6b61b356c0f

EfficientNetV2 Based Ensemble Model for Quality Estimation of Diabetic Retinopathy Images from DeepDRiD

About this item

Full title

EfficientNetV2 Based Ensemble Model for Quality Estimation of Diabetic Retinopathy Images from DeepDRiD

Publisher

Switzerland: MDPI AG

Journal title

Diagnostics (Basel), 2023-02, Vol.13 (4), p.622

Language

English

Formats

Publication information

Publisher

Switzerland: MDPI AG

More information

Scope and Contents

Contents

Diabetic retinopathy (DR) is one of the major complications caused by diabetes and is usually identified from retinal fundus images. Screening of DR from digital fundus images could be time-consuming and error-prone for ophthalmologists. For efficient DR screening, good quality of the fundus image is essential and thereby reduces diagnostic errors....

Alternative Titles

Full title

EfficientNetV2 Based Ensemble Model for Quality Estimation of Diabetic Retinopathy Images from DeepDRiD

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_0f0e066b789e4581871ae6b61b356c0f

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0f0e066b789e4581871ae6b61b356c0f

Other Identifiers

ISSN

2075-4418

E-ISSN

2075-4418

DOI

10.3390/diagnostics13040622

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