Targeted change detection in remote sensing images

نویسندگان

  • Vladimir Ignatiev
  • Alexey Trekin
  • Viktor Lobachev
  • Georgy Potapov
  • Evgeny Burnaev
چکیده

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 propose 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.

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تاریخ انتشار 2018