| Title: | Building detection by local region features in SAR images |
| Issue Date: | Dec-2020 |
| Publisher: | Самарский национальный исследовательский университет |
| Citation: | Ye SP, Chen CX, Nedzved A, Jiang J. Building detection by local region features in SAR images. Computer Optics 2020; 44(6): 944-950. DOI: 10.18287/2412-6179-CO-703. |
| Series/Report no.: | 44;6 |
| 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://dx.doi.org/10.18287/2412-6179-CO-703 http://repo.ssau.ru/jspui/handle/123456789/22589 |
| Appears in Collections: | Журнал "Компьютерная оптика" |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 440612.pdf | Основная статья | 3.11 MB | Adobe PDF | View/Open |
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