Отрывок: They are very complicated procedures that have many realizations. The detection is the process of partitioning a SAR image into multiple regions (connected sets of pixels that corre- spond to objects). The goal of detection is to simplify the representation of an image into more meaningful to analyze. The classification is defining visual content to seg- mented regions. It is final step for detection build...
Название : Building detection by local region features in SAR images
Авторы/Редакторы : Ye, S.P.
Chen, C.X.
Nedzved, A.
Jiang, J.
Ключевые слова : SAR images
building detection
YOLO network
Дата публикации : Дек-2020
Издательство : Самарский национальный исследовательский университет
Библиографическое описание : 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.
Серия/номер : 44;6
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.
URI (Унифицированный идентификатор ресурса) : https://dx.doi.org/10.18287/2412-6179-CO-703
http://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Building-detection-by-local-region-features-in-SAR-images-86858
Другие идентификаторы : Dspace\SGAU\20210106\86858
Располагается в коллекциях: Журнал "Компьютерная оптика"

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