Author: Saban Ozturk; Umut Ozkaya; Mucahid Barstugan
Title: Classification of Coronavirus Images using Shrunken Features Document date: 2020_4_6
ID: 2l1zw19o_43
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.03.20048868 doi: medRxiv preprint For this reason, the feature extraction method is most suitable for hand-crafted methods. However, the fact that the number of images in the dataset is quite low and the number of sample differences between classes is very high (almost 90% belong to only one class) will create a problem for classifier alg.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.03.20048868 doi: medRxiv preprint For this reason, the feature extraction method is most suitable for hand-crafted methods. However, the fact that the number of images in the dataset is quite low and the number of sample differences between classes is very high (almost 90% belong to only one class) will create a problem for classifier algorithms.
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