Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/288229
Title: | Building detection by local region features in SAR images |
Authors: | Ye, S.P. Chen, C.X. Nedzved, A. Jiang, J. |
Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика |
Issue Date: | 2020 |
Publisher: | Institution of Russian Academy of Sciences |
Citation: | Comput Opt 2020;44(6):944-950. |
Abstract: | The buildings are very complex for detection on SAR images, where the basic features of those are shadows. There are many different representations for SAR shadow. As result it is no possible to use convolutional neural network for building detection directly. In this article we give property analysis of SAR shadows of different type buildings. After that, each region (ROI) prepared for training of building detection is corrected with its own SAR shadow properties. Reconstructions of ROI will be put in a modified YOLO network for building detection with better quality result. |
URI: | https://elib.bsu.by/handle/123456789/288229 |
DOI: | 10.18287/2412-6179-CO-703 |
Scopus: | 85098732302 |
Licence: | info:eu-repo/semantics/openAccess |
Appears in Collections: | Статьи факультета прикладной математики и информатики |
Files in This Item:
File | Description | Size | Format | |
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440612.pdf | 3,11 MB | Adobe PDF | View/Open |
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