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Proceedings Paper

Clouds segmentation on panchromatic high spatial resolution remote sensing images using convolutional neural networks
Author(s): V. Eremeev; A. Kuznetcov; A. Kochergin; A. Makarenkov
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Paper Abstract

In the paper is described clouds segmentation algorithm based on convolutional neural network. It has been made an analysis of existed convolutional neural networks topologies and it was made a decision of using the modifying U-Net topology. The preliminary data processing has been made taking into account a source data specific. Learning dataset has been made using real high spatial resolution remote sensing data and manual segmented clouds mask. Methodology of using learning dataset in network learning process has been proposed. Results of learned network implementation on real data are shown in the paper.

Paper Details

Date Published: 7 October 2019
PDF: 6 pages
Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 111552E (7 October 2019); doi: 10.1117/12.2536410
Show Author Affiliations
V. Eremeev, Ryazan State Radio Engineering Univ. (Russian Federation)
A. Kuznetcov, Ryazan State Radio Engineering Univ. (Russian Federation)
A. Kochergin, Ryazan State Radio Engineering Univ. (Russian Federation)
A. Makarenkov, Ryazan State Radio Engineering Univ. (Russian Federation)


Published in SPIE Proceedings Vol. 11155:
Image and Signal Processing for Remote Sensing XXV
Lorenzo Bruzzone; Francesca Bovolo, Editor(s)

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