HIGHLIGHTS
- who: Anita Desiani et al. from the Faculty, Universitas Sriwijaya, Inderalaya, Indonesia have published the article: VG-DropDNet A Robust Architecture for Blood Vessels Segmentation on Retinal Image, in the Journal: (JOURNAL)
- what: This study proposes a VG-DropDNet architecture that combines VGG DenseNet and U-Net with a dropout layer in blood vessels retinal segmentation. The aim of this stage is to produce the best weights that would be used in the testing stage. This study evaluates the performance of the proposed architecture with a confusion matrix is included accuracy (Acc), sensitivity (Se), specificity . . .
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