title: ÐÐ±Ð·Ð¾Ñ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² ÑÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ¾Ð¹ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ ÑÐ¿ÑÑÐ½Ð¸ÐºÐ¾Ð²ÑÑ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² Ð·ÐµÐ¼Ð»Ð¸ Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²ÑÑ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸Ð¹
title: Review of methods of semantic segmentation of satellite images of the earth using neural network technologies
Creators: name: ÐÐ°ÑÐ¾Ð½ÑÐºÐ¾, Ð¯Ð½Ð°
name: ÐÐµÑÑÑÐµÐ²Ð°, ÐÐ»ÐµÐºÑÐ°Ð½Ð´ÑÐ°
name: ÐÐ¾Ð´Ð¼Ð°ÑÑÐºÐ¾Ð²Ð°, ÐÐ¸ÐºÑÐ¾ÑÐ¸Ñ
name: ÐÐ°Ð»Ð°ÐºÑÐ¸Ð¾Ð½Ð¾Ð², ÐÐ³Ð¾ÑÑ
name: ÐÐ¼Ð¸ÑÑÐ¸ÐµÐ²Ð°, ÐÐ¸Ð´Ð¸Ñ
name: "Ð¡Ð¸ÑÑÐµÐ¼Ð½ÑÐ¹ Ð°Ð½Ð°Ð»Ð¸Ð· Ð² Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ð¸ Ð¸ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ð¸", Ð¼ÐµÐ¶Ð´ÑÐ½Ð°ÑÐ¾Ð´Ð½Ð°Ñ Ð½Ð°ÑÑÐ½Ð¾-Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ°Ñ ÐºÐ¾Ð½ÑÐµÑÐµÐ½ÑÐ¸Ñ (26; 2022; Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³)
Publisher: name: ÐÐÐÐÐ¢ÐÐ¥-ÐÐ ÐÐ¡Ð¡
Year: 2023
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÐ°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ°Ð·Ð¼ÐµÑÐºÐ°
ÑÐºÐ¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ð¹ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³
ÐºÐ¾ÑÐ¼Ð¸ÑÐµÑÐºÐ¸Ðµ ÑÐ½Ð¸Ð¼ÐºÐ¸
Ð´Ð°ÑÐ°ÑÐµÑ
markup
environmental monitoring
satellite images
dataset

description: Ð Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð° Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ð° ÑÐºÐ¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³Ð° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÐºÐ¾ÑÐ¼Ð¸ÑÐµÑÐºÐ¸Ñ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² ÑÐ°Ð·Ð½Ð¾Ð¹ ÑÐ¾ÑÐ½Ð¾ÑÑÐ¸ Ð½Ð° Ð¿ÑÐ¸Ð¼ÐµÑÐµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ â Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ ÑÐ°Ð·Ð½ÑÑ
ÐºÐ»Ð°ÑÑÐ¾Ð² Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð¸ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³Ð° ÑÐ¾ÑÑÐ¾ÑÐ½Ð¸Ñ Ð¾ÐºÑÑÐ¶Ð°ÑÑÐµÐ¹ ÑÑÐµÐ´Ñ. ÐÐ½Ð¾Ð³Ð¸Ðµ Ð»Ð¾ÐºÐ°Ð»ÑÐ½ÑÐµ Ð¸ Ð³Ð»Ð¾Ð±Ð°Ð»ÑÐ½ÑÐµ ÑÐºÐ¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ðµ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð¼Ð¾Ð³ÑÑ Ð±ÑÑÑ Ð²ÑÑÐ²Ð»ÐµÐ½Ñ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÑÐ¿ÑÑÐ½Ð¸ÐºÐ¾Ð²ÑÑ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² ÑÐ°Ð·Ð½Ð¾Ð¹ Ð´ÐµÑÐ°Ð»ÑÐ½Ð¾ÑÑÐ¸: Ð²ÑÑÐ¾ÐºÐ¾Ð³Ð¾ Ð¸ Ð½Ð¸Ð·ÐºÐ¾Ð³Ð¾ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ. Ð¡Ð½Ð¸Ð¼ÐºÐ¸ Ð²ÑÑÐ¾ÐºÐ¾Ð³Ð¾ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑ Ð´Ð»Ñ Ð¼Ð¾Ð½Ð¸ÑÐ¾ÑÐ¸Ð½Ð³Ð° Ð»Ð¾ÐºÐ°Ð»ÑÐ½ÑÑ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼, Ð½Ð°Ð¿ÑÐ¸Ð¼ÐµÑ Ð·Ð¾Ð½Ñ Ð²ÑÑÑÐ±ÐºÐ¸ Ð²Ð±Ð»Ð¸Ð·Ð¸ Ð³Ð¾ÑÐ¾Ð´Ð¾Ð², Ð° Ð½Ð¸Ð·ÐºÐ¾Ð³Ð¾ ÑÐ°Ð·ÑÐµÑÐµÐ½Ð¸Ñ â Ð´Ð»Ñ Ð±Ð¾Ð»ÑÑÐµÐ³Ð¾ Ð¾ÑÐ²Ð°ÑÐ° ÑÐµÑÑÐ¸ÑÐ¾ÑÐ¸Ð¸, Ð½Ð°Ð¿ÑÐ¸Ð¼ÐµÑ Ð·Ð¾Ð½Ñ Ð¿Ð¾Ð¶Ð°ÑÐ¾Ð². Ð ÑÐ°Ð¼ÐºÐ°Ñ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð±ÑÐ»Ð¸ Ð¿ÑÐ¾Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ñ ÑÑÐ°ÑÑÐ¸ Ð±Ð°Ð·Ñ Ð½Ð°ÑÑÐ½ÑÑ Ð¿ÑÐ±Ð»Ð¸ÐºÐ°ÑÐ¸Ð¹ Scopus. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð´Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ Ð¼Ð¾Ð³ÑÑ Ð±ÑÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ñ ÑÑÐºÐ¾Ð²Ð¾Ð´Ð¸ÑÐµÐ»ÑÐ¼Ð¸ Ð¿Ð¾Ð´ÑÐ°Ð·Ð´ÐµÐ»ÐµÐ½Ð¸Ð¹ Ð¿ÑÐ¸ Ð¿Ð¾Ð´Ð±Ð¾ÑÐµ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ° Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð¾ÑÐ´ÐµÐ»ÑÐ½ÑÑ ÑÑÐ°ÑÑÐºÐ¾Ð², ÑÑÐ¸ÑÑÐ²Ð°Ñ ÑÐ°Ð·Ð½ÑÐµ ÐºÐ»Ð°ÑÑÑ, Ð·Ð°Ð´Ð°ÑÐ¸ Ð¸ Ð¾ÑÑÐ°ÑÐ»Ð¸.
description: In this paper, the problem of environmental monitoring using space images of different accuracy is considered on the example of using machine learning â neural networks for recognizing different classes of objects and monitoring the state of the environment. Many local and global environmental problems can be identified using satellite images of different detail: high and low resolution. High-resolution images are used to monitor local problems, for example, clear-cut areas near cities, and low-resolution images are used to cover a larger area, for example, fire zones. As part of the study, articles from the Scopus database of scientific publications were analyzed. The results of this study can be used by department heads when selecting a modeling tool to solve the problems of segmenting and classifying individual sections, taking into account different classes, tasks and industries.