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- W4382631864 abstract "In this work, we propose a multi-task learning-based approach towards the localization of optic disc and fovea from human retinal fundus images using a deep learning-based approach. Formulating the task as an image-based regression problem, we propose a Densenet121-based architecture through an extensive set of experiments with a variety of CNN architectures. Our proposed approach achieved an average mean absolute error of only 13pixels (0.04%), mean squared error of 11 pixels (0.005%), and a root mean square error of only 0.02 (13%) on the IDRiD dataset." @default.
- W4382631864 created "2023-07-01" @default.
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- W4382631864 date "2023-06-29" @default.
- W4382631864 modified "2023-09-25" @default.
- W4382631864 title "A Deep Learning-Based Approach Towards Simultaneous Localization of Optic Disc and Fovea from Retinal Fundus Images" @default.
- W4382631864 doi "https://doi.org/10.3233/shti230575" @default.
- W4382631864 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37387109" @default.
- W4382631864 hasPublicationYear "2023" @default.
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