Targeted change detection in remote sensing images

V. Ignatiev, A. Trekin, V. Lobachev, G. Potapov, E. Burnaev

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    8 Citations (Scopus)

    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.

    Original languageEnglish
    Title of host publicationEleventh International Conference on Machine Vision, ICMV 2018
    EditorsPetia Radeva, Antanas Verikas, Jianhong Zhou, Dmitry P. Nikolaev
    PublisherSPIE
    ISBN (Electronic)9781510627482
    DOIs
    Publication statusPublished - 2019
    Event11th International Conference on Machine Vision, ICMV 2018 - Munich, Germany
    Duration: 1 Nov 20183 Nov 2018

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume11041
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Conference

    Conference11th International Conference on Machine Vision, ICMV 2018
    Country/TerritoryGermany
    CityMunich
    Period1/11/183/11/18

    Keywords

    • change detection
    • computer vision
    • deep learning
    • remote sensing
    • satellite imagery

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