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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/45855
Title: DSDNet Neural Network for Shadow Detection from Urban Satellite Images
Authors: Naidovich, O.
Nedzved, A.
Shiping Ye
Keywords: материалы конференций;conference proceedings;shadow detection;DSDNet;deep neural networks;segmentation;Satellite image
Issue Date: 2021
Publisher: UIIP NASB
Citation: DSDNet Neural Network for Shadow Detection from Urban Satellite Images / Naidovich O., Nedzved A., Shiping Ye // Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021) : Proceedings of the 15th International Conference, 21–24 Sept. 2021, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2021. – P. 191–194.
Abstract: Shadow detection is one of the fundamental and challenging tasks in the field of computer vision and image processing. The increase of computing power has enabled many deep learning approaches to solve this problem. In this article we consider a DSDNet neural network in order to detect shadows on the base of texture analysis of the shadow area and bright area of the urban area.
URI: https://libeldoc.bsuir.by/handle/123456789/45855
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2021) = Распознавание образов и обработка информации (2021)

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