ГРНТИ 50.07 Теоретические основы вычислительной техники
ББК 3297 Вычислительная техника
The paper deals with the algorithms of building recognition in air and satellite photos. The use of convolutional artificial neural networks to solve the problem of image segmentation is substantiated. The choice between two architectures of artificial neural networks is considered. The development of software implementing building recognition based on convolutional neural networks is described. The architecture of the software complex, some features of its construction and interaction with the cloud geo-information platform in which it functions are described. The application of the developed software for the recognition of buildings in images is described. The results of experiments on building recognition in pictures of various resolutions and types of buildings using the developed software are analysed.
Earth remote sensing, building recognition in photos, convolutional neural networks, semantic picture segmentation
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7. 2015 IEEE GRSS Data Fusion Contest Resultshttp://www.grss-ieee.org/community/technicalcommittees/data-fusion/2015-ieee-grss-data-fusioncontest-results/
8. 2016 IEEE GRSS Data Fusion Contest Resultshttp://www.grss-ieee.org/community/technicalcommittees/data-fusion/2016-ieee-grss-data-fusioncontest-results/
9. 2017 IEEE GRSS Data Fusion Contest Resultshttp://www.grss-ieee.org/community/technicalcommittees/data-fusion/2017-ieee-grss-data-fusioncontest-results/
10. 2018 IEEE GRSS Data Fusion Contest Resultshttp://www.grss-ieee.org/community/technicalcommittees/data-fusion/2018-ieee-grss-data-fusioncontest-results/
