Dielectric Cylinder Discrimination with ANN Using Wideband Electromagnetic Response

Oleg Drobakhin*, Vasil Tabatadze, Vladyslav Chuchva, Artem Huz

*Corresponding author for this work

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

Abstract

The application of three-component stacked artificial neural networks (ANN) for discrimination of dielectric cylinders of different diameters by their radio images is considered. Neural networks include two sparse autoencoders and the softmax unit. Neural networks are not tied to the frequency range, unlike many well-known methods based on the resonant properties of objects, and they are a powerful tool for object recognition. Radio images were obtained using the method of auxiliary sources (MAS) for cylinders with the radius of 15 to 35 mm. The possibility of successful recognition was confirmed for the case of the diameter deviation of 1 mm and the presence of additive Gaussian noise with SNR of up to 5 dB.

Original languageEnglish
Title of host publication2023 IEEE 28th International Seminar/Workshop - Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory, DIPED 2023 - Proceedings
PublisherIEEE Computer Society
Pages133-137
Number of pages5
ISBN (Electronic)9798350315332
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event28th IEEE International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory, DIPED 2023 - Tbilisi, Georgia
Duration: 11 Sept 202313 Sept 2023

Publication series

NameProceedings of International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory, DIPED
Volume2023-September
ISSN (Print)2165-3585
ISSN (Electronic)2165-3593

Conference

Conference28th IEEE International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory, DIPED 2023
Country/TerritoryGeorgia
CityTbilisi
Period11/09/2313/09/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • artificial neural networks
  • autoencoder
  • dielectric cylinders
  • discrimination of targets
  • method of auxiliary sources (MAS)
  • radio images
  • softmax

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