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- W3009772007 abstract "In this study, the problem of detecting pneumonia in chest x-ray images is addressed. The method used is based on the computation of locally adaptive regression kernel (LARK) descriptors, which, when used in conjunction with the novel Support Vector Machine (SVM) classifier, obtained a 98% precision and 98% recall tested in only 400 images and a 96% precision and 95% recall tested in 1000 images in a chest x-ray images dataset. Different sample sizes were also tested to show that the method is robust even with a small sample size. This method was also shown to obtain better performance compared to two other classifiers, namely Random Forest (RF) and decision trees (DT)." @default.
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- W3009772007 date "2020-01-01" @default.
- W3009772007 modified "2023-10-18" @default.
- W3009772007 title "Locally Adaptive Regression Kernels and Support Vector Machines for the Detection of Pneumonia in Chest X-Ray Images" @default.
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- W3009772007 doi "https://doi.org/10.1007/978-3-030-42058-1_11" @default.
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