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Targeted change detection in remote sensing images
Author(s): V. Ignatiev; A. Trekin; V. Lobachev; G. Potapov; E. Burnaev
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Paper Abstract

Recent developments in the remote sensing systems and image processing made it possible to propose a new method of the object classification and detection of the specific changes in the series of satellite Earth images (so called targeted change detection). In this paper we develop a formal problem statement that allows to use effectively the deep learning approach to analyze time-dependent series of remote sensing images. We also introduce a new framework for the development of deep learning models for targeted change detection and demonstrate some cases of business applications it can be used for.

Paper Details

Date Published: 15 March 2019
PDF: 6 pages
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110412H (15 March 2019); doi: 10.1117/12.2523141
Show Author Affiliations
V. Ignatiev, Skoltech Institute of Science and Technology (Russian Federation)
A. Trekin, Skoltech Institute of Science and Technology (Russian Federation)
V. Lobachev, Skoltech Institute of Science and Technology (Russian Federation)
G. Potapov, Skoltech Institute of Science and Technology (Russian Federation)
E. Burnaev, Skoltech Institute of Science and Technology (Russian Federation)


Published in SPIE Proceedings Vol. 11041:
Eleventh International Conference on Machine Vision (ICMV 2018)
Antanas Verikas; Dmitry P. Nikolaev; Petia Radeva; Jianhong Zhou, Editor(s)

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