точність класифікації

Classification of vibroartographic signals based on wavelet transformation and machine learning techniques

Vibroartography is a method of medical diagnosis, designed for objective estimation of human joint motor function in general and arthrokinematics of the knee joint in particular. The method is based on the analysis of signals of vibroacoustic emission. Vibroartography is not so effective compared to methods such as radiography and magnetic resonance imaging (MRI), but it is definitely a sensitive method for assessing the degree of knee joint dysfunction. This paper presents the research results related to the design of a system for vibroarthrographic signals computer processing.

Application of artificial neural networks for classifying surface areas with a certain relief

The purpose of research. The main purpose of research is to analyze the relief of  various surfaces. For example, to select on the surface the individual sections of a certain  form, such as slopes that are oriented in a given direction. The main aim of the article is the use of artificial neural networks (ANN). To solve the problem of classification a binary classifier was created and its work and its accuracy was studied. Method. The research was carried out on the certain section of the earth's surface. The digital model, presented by greed file, was created.