CNN-Based deep learning architecture for electromagnetic imaging of rough surface profiles

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dc.authorid0000-0002-8428-4404
dc.authorid0000-0001-5168-4367
dc.authorid0000-0003-2966-5623
dc.contributor.authorAydın, İzdeen_US
dc.contributor.authorBudak, Güvenen_US
dc.contributor.authorSefer, Ahmeten_US
dc.contributor.authorYapar, Alien_US
dc.date.accessioned2022-09-01T13:06:08Z
dc.date.available2022-09-01T13:06:08Z
dc.date.issued2022-10
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Electrical-Electronics Engineeringen_US
dc.description.abstractA convolutional neural network (CNN) based deep learning (DL) technique for electromagnetic imaging of rough surfaces separating two dielectric media is presented. The direct scattering problem is formulated through the conventional integral equations and the synthetic scattered field data is produced by a fast numerical solution technique which is based on Method of Moments (MoM). Two different special CNN architectures are designed and implemented for the solution of the inverse rough surface imaging problem wherein both random and deterministic rough surface profiles can be imaged. It is shown by a comprehensive numerical analysis that the proposed deep-learning (DL) inversion scheme is very effective and robust.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationAydın, İ., Budak, G., Sefer, A. & Yapar, A. (2022). CNN-Based deep learning architecture for electromagnetic imaging of rough surface profiles. IEEE Transactions on Antennas and Propagation, 70(10), 9752-9763. doi:10.1109/TAP.2022.3177493en_US
dc.identifier.doi10.1109/TAP.2022.3177493
dc.identifier.endpage9763
dc.identifier.issn0018-926X
dc.identifier.issn1558-2221
dc.identifier.issue10
dc.identifier.startpage9752
dc.identifier.urihttps://hdl.handle.net/11729/4811
dc.identifier.urihttp://dx.doi.org/10.1109/TAP.2022.3177493
dc.identifier.volume70
dc.identifier.wosWOS:000880709700101
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorSefer, Ahmeten_US
dc.institutionauthorid0000-0001-5168-4367
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE Transactions on Antennas and Propagationen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectConvolutional neural networken_US
dc.subjectDeep learningen_US
dc.subjectElectromagneticsen_US
dc.subjectElectromagneticsen_US
dc.subjectImagingen_US
dc.subjectInverse problemsen_US
dc.subjectInverse scattering problemsen_US
dc.subjectRough surface imagingen_US
dc.subjectRough surfacesen_US
dc.subjectSurface roughnessen_US
dc.subjectSurface treatmenten_US
dc.subjectSurface wavesen_US
dc.subjectConvolutionen_US
dc.subjectIntegral equationsen_US
dc.subjectMethod of momentsen_US
dc.subjectNetwork architectureen_US
dc.subjectNeural networksen_US
dc.subjectNumerical methodsen_US
dc.subjectSurface measurementen_US
dc.subjectSurface scatteringen_US
dc.subjectNetwork-baseden_US
dc.subjectSurface imagingen_US
dc.subjectInverse scatteringen_US
dc.subjectNeural-networken_US
dc.subjectReconstructionen_US
dc.subjectClassificationen_US
dc.subject2-Den_US
dc.titleCNN-Based deep learning architecture for electromagnetic imaging of rough surface profilesen_US
dc.typeArticleen_US

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