Journal of Sensors and Sensor Systems
Journal of Sensors and Sensor Systems
JSSS
Articles | Volume 10, issue 1
Articles | Volume 10, issue 1
https://doi.org/10.5194/jsss-10-127-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/jsss-10-127-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 1
Regular research article
 | 
01 Jun 2021
Regular research article |  | 01 Jun 2021

A classification technique of civil objects by artificial neural networks using estimation of entropy on synthetic aperture radar images

Anton V. Kvasnov and Vyacheslav P. Shkodyrev
Publisher's note: due to licence issues, Figs. 3–6 have been exchanged in the published article. Apart from that, the word group has been changed to civil throughout the text. The handling associate editor and the handling chief editor approved the changes.

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Short summary
We have prepared an article that demonstrates one of the ways to recognize objects on the ground surface. This paper is a result of experimental data that were collected with unnamed aerial vehicles (UAVs) with synthetic aperture radar. Although UAV radar has a small monitoring area, we noted that such pictures can contain the steady features of the mutual arrangement between detected objects. We have constructed an artificial neural network that solves the tasks of group object recognition.
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