Autoencoder Guided Low-Rank Approximation Approach for Clutter Removal in GPR Images

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dc.contributor.authorKayacan, Yavuz Emre
dc.contributor.authorErer, Isin
dc.date.accessioned2025-03-09T10:57:33Z
dc.date.available2025-03-09T10:57:33Z
dc.date.issued2024
dc.departmentİstanbul Beykent Üniversitesi
dc.description47th International Conference on Telecommunications and Signal Processing, TSP 2024 -- 10 July 2024 through 12 July 2024 -- Virtual, Online -- 201450
dc.description.abstractThe performance of low-rank and sparse decomposition (LRSD) based clutter removal methods which are widely used in GPR systems depends heavily on the regularization parameter. This study proposes a A parameter-free low-rank approach. The low-rank component recovered by an autoencoder (AE) network is subtracted from the raw image to provide a clutter-free image. Simulation and experimental results validate the superiority of the proposed method compared to the low-rank approach Nonnegative Matrix Factorization (NMF) as well as other LRSD methods: Robust Principal Component Analysis (RPCA), Robust NMF (RNMF), and Robust Autoencoder (RAE). © 2024 IEEE.
dc.description.sponsorshipTürkiye Bilimsel ve Teknolojik Araştırma Kurumu, TÜBİTAK, (120E234)
dc.identifier.doi10.1109/TSP63128.2024.10605982
dc.identifier.endpage335
dc.identifier.isbn979-835036559-7
dc.identifier.scopus2-s2.0-85201159319
dc.identifier.scopusqualityN/A
dc.identifier.startpage332
dc.identifier.urihttps://doi.org/10.1109/TSP63128.2024.10605982
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4911
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2024 47th International Conference on Telecommunications and Signal Processing, TSP 2024
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250310
dc.subjectautoencoder
dc.subjectclutter removal
dc.subjectGround Penetrating Radar (GPR)
dc.subjectlow-rank approximation
dc.subjectnonnegative matrix factorization (NMF)
dc.titleAutoencoder Guided Low-Rank Approximation Approach for Clutter Removal in GPR Images
dc.typeConference Object

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