Pub Date : 1900-01-01DOI: 10.23919/USNC-URSI-NRSM.2019.8713113
Daniel Ospina Acero, S. Chowdhury, F. Teixeira, Q. Marashdeh
We apply the Adaptive Relevance Vector Machine to automatically select the measurement set in a tomographic setting, from all the arrangements or combinations of the measuring elements, that yield the lowest level of uncertainty about the estimated results, while maintaining good image reconstruction. To illustrate the proposed method, we present simulation results derived from Electrical Capacitance Tomography.
{"title":"Automatic Sensor Reconfiguration based on Adaptive Relevance Vector Machine for Uncertainty Reduction in Tomography Imaging","authors":"Daniel Ospina Acero, S. Chowdhury, F. Teixeira, Q. Marashdeh","doi":"10.23919/USNC-URSI-NRSM.2019.8713113","DOIUrl":"https://doi.org/10.23919/USNC-URSI-NRSM.2019.8713113","url":null,"abstract":"We apply the Adaptive Relevance Vector Machine to automatically select the measurement set in a tomographic setting, from all the arrangements or combinations of the measuring elements, that yield the lowest level of uncertainty about the estimated results, while maintaining good image reconstruction. To illustrate the proposed method, we present simulation results derived from Electrical Capacitance Tomography.","PeriodicalId":142320,"journal":{"name":"2019 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM)","volume":"32 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120902461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}