The Kohonen type neural network in the process of identification of orchard pests

One of advantages of suggest a procedure is the ability of the Kohonen neural network to determine the degree of similarity occurring between classes. The Kohonen network can be also used to detect regularities occurring in the obtained empirical data. If at the network input, a new unknown case appears which the network is unable to recognise, it means that it is different from all the classes known previously. The Kohonen network taught in this way can serve as a detector signalling the appearance of a widely understood novelty. Such a network can also look for similarities between the known data and the noisy data. In this way, it is able to identify fragments of images presenting photographs of e.g. orchard pests.