The Messidor-2 set is a benchmark for algorithms that detect diabetic retinopathy. We randomly sampled the Kaggle EyePACS data set consisting of 88 702 images into a training and validation set of 57 146 images and a test set of 8790 images.
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Feb 16, 2016 · Reposting from answer to Where on the web can I find free samples of Big Data sets, of, e.g., countries, cities, or individuals, to analyze? This link list, available on Github, is quite long and thorough: caesar0301/awesome-public-datasets You wi...
Feb 16, 2016 · Reposting from answer to Where on the web can I find free samples of Big Data sets, of, e.g., countries, cities, or individuals, to analyze? This link list, available on Github, is quite long and thorough: caesar0301/awesome-public-datasets You wi...
5.2. Cross-dataset validation — training on Kaggle and testing on Messidor-2 and DR2. After refining the automated solution for referable diabetic retinopathy screening from scratch, we investigate the performance over distinct datasets.

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Nov 30, 2016 · Using the latest tools in machine learning, scientists at Google have taught a computer algorithm to screen for diabetic retinopathy with sensitivity and specificity rivalling that of ...
The second test set was the publicly available Messidor-2 data set [ 5 ] [ 6 ], consisting of 1748 images. This data set was acquired between January 2005 and December 2010 at three hospitals in France by using a Topcon TRC NW6 non-mydriatic camera and 45 degrees fields of view centered on the fovea.

Messidor 2 kaggle

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