RECOGNITION AND CLASSIFICATION OF NATURAL RESOURCE IMAGES IN SATELLITE IMAGES USING THE NEURAL NETWORK ALGORITHM

Authors

  • Evgeniy Popov Nizhny Novgorod State University of Architecture and Civil Engineering, Nizhny Novgorod
  • Pavel Yurchenko Nizhny Novgorod State University of Architecture and Civil Engineering, Nizhny Novgorod

DOI:

https://doi.org/10.14529/build250209

Keywords:

, image recognition and classification, satellite images, neural network, natural resources

Abstract

The paper describes an algorithm for recognizing and classifying natural resource images in satellite images using machine learning methods with a tutor. Four different approaches were used to train the training dataset: Gaussian Mixture Model, Random Forest, Support Vector Machines, and K-Nearest Neighbors. The parameters of the neural network architecture were experimentally established, which allows classifying natural resources with maximum accuracy

Author Biographies

Evgeniy Popov, Nizhny Novgorod State University of Architecture and Civil Engineering, Nizhny Novgorod

Doctor of Engineering Sciences, Professor of the Department of Engineering Graphics and Information Modeling

Pavel Yurchenko, Nizhny Novgorod State University of Architecture and Civil Engineering, Nizhny Novgorod

postgraduate student of the Department of Engineering Graphics and Information Modeling

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Published

2025-07-29

Issue

Vol. 25 No. 2 (2025): Строительство и архиетктура

Section

Инженерная геометрия и компьютерная графика. Цифровая поддержка жизненного цикла изделий