Comparing Svm And Naïve Bayes Classifier For Automatic Microaneurysm Detections release_u42xoaq5tvffnnbpxogheuligi

by A. Sopharak, B. Uyyanonvara, S. Barman

Published by Zenodo.

(2014)

Abstract

Diabetic retinopathy is characterized by the development of retinal microaneurysms. The damage can be prevented if disease is treated in its early stages. In this paper, we are comparing Support Vector Machine (SVM) and Naïve Bayes (NB) classifiers for automatic microaneurysm detection in images acquired through non-dilated pupils. The Nearest Neighbor classifier is used as a baseline for comparison. Detected microaneurysms are validated with expert ophthalmologists' hand-drawn ground-truths. The sensitivity, specificity, precision and accuracy of each method are also compared.
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Type  article-journal
Stage   published
Date   2014-04-06
Language   en ?
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