Modelling a neural network for analysing the results of segmentation of satellite images - Kaldarova, Mira; Akanova, Akerke; Naizagarayeva, Akgul; Kazanbayeva, Albina; Ospanova, Nazira (Indonesian Journal of Electrical Engineering and Computer Science, 2024)
The study's relevance lies in addressing inaccuracies within satellite image segmentation, necessitating the development and implementation of neural network models for automated segmentation. The purpose of study is to develop a model of a neural network for training with data obtained from the segmentation of satellite images. The basis of the methodological approach in study is a combination of methods of system analysis of neural networks, which have had a substantial impact on the development of the computer vision industry, with an empirical study of the general principles of neural network modelling for the training on satellite images segmentation. In this study, the results were obtained, indicating that there is a fundamental possibility of developing and practical implementation of a neural network model to determine the quality of the obtained segmentation of images of agricultural fields. Satellite images of agricultural fields of the Republic of Kazakhstan are obtained, and segmentation of field images is performed using the developed neural network model for learning segmentation results. The practical importance of the results obtained in study lies in the possibility of their use in the development of functional models of neural networks for training the results of the segmentation of satellite images.