In this paper machine learning methods are studied for classification data containing some misleading items. We use ensembles of known noise correction preprocessing the training set. Preprocessing can be either relabeling or deleting items detected to have noisy labels. After preprocessing, usual convolutional networks applied data. With performance very accurate further improved.

It has been used extensively for detection of heart disease. ECG is non-stationary bioelectrical signal including valuable clinical information, but frequently the valuable clinical information is corrupted by various kinds of noise. The main sources of noise are: power-line interference from 50–60 Hz pickup and harmonics from the power mains; baseline wanders caused by variable contact between...

Detecting edges in piecewise smooth images is important in a variety of applications. In some cases, such as magnetic resonance imaging, data are collected as Fourier samples, and are often over-sampled at low frequencies but more sparsely acquired in the high frequency range. This under-sampling causes Fourier based edge detection algorithms to yield false positives in smooth regions. The prob...

hemophilia b is factor ix deficiency and is inherited as x-linked recessive disorder. the subject of carrier detection in hemophilias has received new impetus in the last several years. analysis of factor ix gene polymorphisms is considered the best approach for prenatal diagnosis and hemophilia b carrier detection, if the identification of the gene mutation is possible. allele frequencies of t...

It is well known that damaged structural members may alter the behavior of the structures considerably. Careful observation of these changes has often been viewed as a means to identify and assess the location and severity of damages in structures. Among the responses of a structure, natural frequencies are both relatively easy to obtain and independent from external excitation, and therefore, ...