Порівняльний аналіз нейромережевих методів в задачах класифікації об'єктів

Abstract

Neural Networks based approach to object classifying is considered. The main difficulties of the object classification problem are analyzed. Such classification problems as binary are considered, as well as the task of classifying objects of the same type, which are subclassed by their characteristic features. Different types of classic and deep neural networks are described. The advantages and disadvantages of neural networks and deep neural networks are described. An example of the second type task is the classification of apples by their varieties. It is supposed to split this type of object into 13 classes. The use of convolutional neural networks for the task of classifying apples by varieties is substantiated.