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ЖУРНАЛЫ // Компьютерная оптика // Архив

Компьютерная оптика, 2020, том 44, выпуск 6, страницы 944–950 (Mi co868)

Эта публикация цитируется в 6 статьях

ОБРАБОТКА ИЗОБРАЖЕНИЙ, РАСПОЗНАВАНИЕ ОБРАЗОВ

Building detection by local region features in SAR images

Sh. Yeab, Ch. X. Chena, A. Nedzvedzc, J. Jiangd

a College of Information Science and Technology, Zhejiang Shuren University, Zhejiang, China
b School of Earth Sciences, Zhejiang University, Zhejiang, China
c Department of Computer Applications and Systems, Belarusian State University, Minsk, Belarus
d College of Information Science and Electronic Engineering, Zhejiang University, Zhejiang, China

Аннотация: 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.

Ключевые слова: SAR images, building detection, YOLO network.

Поступила в редакцию: 14.02.2020
Принята в печать: 17.10.2020

DOI: 10.18287/2412-6179-CO-703



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