diabetic retinopathy is one of the most important reasons of blindness which causes serious damage in the retina. the aim of this research is to detect one lesions of the retina, named exudates automatically with image processing techniques. preprocessing is the first step of proposed algorithm. after preprocessing, the optic disc was detected and removed from the retinal image due to the same ...

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.

BACKGROUND Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise. NEW METHOD The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio ...

Background: Magnetoencephalography (MEG) provides a direct measure of brain activity with high combined spatiotemporal resolution. Preprocessing is necessary to reduce contributions from environmental interference and biological noise. New method: The effect on the signal-to-noise ratio of different preprocessing techniques is evaluated. The signal-to-noise ratio (SNR) was defined as the ratio ...

Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches that have been successfully applied to multispectral data are not as effective for hyperspectral data as well. Various investigations indicate that the key problem that causes poor performance in the stochastic approaches t...

This research is to propose a preprocessing method in a data classification process to improve the accuracy of the classification process. The preprocessing method to be used basically aims to clean up the data by forming prototype data generated from the clustering process. It is expected that the proposed preprocessing methods can be used in a variety of data forms and classification algorith...