land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...

In this paper, first, an initial feature vector for vocal fold pathology diagnosis is proposed. Then, for optimizing the initial feature vector, a genetic algorithm is proposed. Some experiments are carried out for evaluating and comparing the classification accuracies which are obtained by the use of the different classifiers (ensemble of decision tree, discriminant analysis and K-nearest neig...

Face recognition is still an active pattern analysis topic. Faces have already been treated as objects or textures, but human face recognition system takes a different approach in face recognition. People refer to faces by their most discriminant features. People usually describe faces in sentences like ``She's snub-nosed'' or ``he's got long nose'' or ``he's got round eyes'' and so like. These...

According to the fundamental goal of remote sensing technology, the image classification of desired sensors can be introduced as the most important part of satellite image interpretation. There exist various algorithms in relation to the supervised land use classification that the most pertinent one should be determined. Therefore, this study has been conducted to determine the best and most su...

conclusions in this study, we proposed a new computer aided diagnostic tool for the detection and classification of breast cancer. the obtained results showed that the proposed method is more reliable in diagnostic to assist the radiologists in the detection of abnormal data and to improve the diagnostic accuracy. results after classification with the ensemble supervised algorithm, the performa...