Electromagnetic Classification

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dc.contributor.authorSimsek, Ergun
dc.date.accessioned2024-09-04T19:58:34Z
dc.date.available2024-09-04T19:58:34Z
dc.date.issued2024-09-30
dc.description2024 IEEE International Symposium on Antennas and Propagation and INC/USNC‐URSI Radio Science Meeting, 14-19 July 2024, Firenze, Italy
dc.description.abstractRather than reconstructing the properties or parameters of a medium as it is done in electromagnetic inversion, this work aims to classify objects with neural networks that are trained with scattered field data and labels (classes). The study demonstrates the feasibility of achieving an 86% accuracy, showcasing potential applications in robotics and environmental perception.
dc.description.urihttps://ieeexplore.ieee.org/document/10687184
dc.format.extent2 pages
dc.genreconference papers and proceedings
dc.genrepostprints
dc.identifierdoi:10.13016/m2jamh-wnq4
dc.identifier.citationSimsek, Ergun. “Electromagnetic Classification.” 2024 IEEE International Symposium on Antennas and Propagation and INC/USNC‐URSI Radio Science Meeting (AP-S/INC-USNC-URSI), July 2024, 899–900. https://doi.org/10.1109/AP-S/INC-USNC-URSI52054.2024.10687184.
dc.identifier.urihttp://hdl.handle.net/11603/35974
dc.identifier.urihttps://doi.org/10.1109/AP-S/INC-USNC-URSI52054.2024.10687184
dc.language.isoen_US
dc.publisherIEEE
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Data Science
dc.rights© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.titleElectromagnetic Classification
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0001-9075-7071

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