title: ÐÐ½Ð°Ð»Ð¸Ð· ÑÐ¿ÑÑÐ½Ð¸ÐºÐ¾Ð²ÑÑ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² Ð³Ð¾ÑÐ¾Ð´Ð¾Ð² Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐ²ÑÑÑÐ¾ÑÐ½ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: The analysis of city satellite images using convolutional neural networks
Creators: name: Ð ÑÑÐ°ÐºÐ¾Ð², ÐÐ³Ð¾Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2021
Subjects: ÑÐ²ÑÑÑÐ¾ÑÐ½ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ¿ÑÑÐ½Ð¸ÐºÐ¾Ð²ÑÐµ ÑÐ½Ð¸Ð¼ÐºÐ¸
Ð³Ð¾ÑÐ¾Ð´ÑÐºÐ°Ñ ÑÑÐµÐ´Ð°
convolutional neural networks
machine learning
satellite imagery
urban environment

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description: The topic of final qualifying work: Â«The analysis of city satellite imagery using convolutional neural networksÂ» The problem of satellite imagery analysis differs from other general image classification problems. The difference reason is satellite imagery nature itself, which makes stated area an interesting object for research. The aim of the work: to investigate the possibility of applying machine-learning technology, convolutional neural networks in particular, to the landuse classification of task of urban areas. Several issues were specified for achieving the work aim: â¢ Specify the neural network architecture â¢ Acquire the learning data for convolutional neural network â¢ Conduct model learning and testing Work results: the work was divided into several stages: data search and processing, neural network architecture development, network learning and result analysis. As a result six datasets were con-structed for six European cities and one common dataset. The maximum classification accuracy 0.75 was achieved, which is a promising result, showing the effectivity of chosen approach to solving the problem. The scope of appliance: urban studies, urban and suburban areas design and development.