Abstract
Machine learning methods for identification of territories near railway infrastructure facilities are considered. The main sources of initial data are presented, as well as algorithms for assessing the quality of the results for landscape elements automated identification using the forest vegetation example. Forest vegetation state identification is carried out based on spectral-brightness characteristics determined using multispectral aerospace imaging materials. Quality indicators for the results of survey materials automated processing and algorithms for calculating the considered indicators are proposed. Examples are given to assess the results quality of using machine learning methods.
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