In this work, a classification approach for three-dimensional subsurface sensing has been presented. The approach is based on a SVM-based classification algorithm for defining an occupancy map of the area under investigation. In order to deal with 3D scenarios, allowing a suitable spatial resolution without adding further measurements or processing, the algorithm has been integrated into a multi-step zooming procedure. The potentialities of the proposed approach have been assessed by means of a numerical validation with blurred synthetic data. Although preliminary, the obtained results suggest that an extension to real on-line 3D cases is worth to be pursued.

Three dimensional electromagnetic sub-surface sensing by means of a multi-step SVM-based classification technique

Donelli, Massimo;Benedetti, Manuel;Rocca, Paolo;Melgani, Farid;Massa, Andrea
2007-01-01

Abstract

In this work, a classification approach for three-dimensional subsurface sensing has been presented. The approach is based on a SVM-based classification algorithm for defining an occupancy map of the area under investigation. In order to deal with 3D scenarios, allowing a suitable spatial resolution without adding further measurements or processing, the algorithm has been integrated into a multi-step zooming procedure. The potentialities of the proposed approach have been assessed by means of a numerical validation with blurred synthetic data. Although preliminary, the obtained results suggest that an extension to real on-line 3D cases is worth to be pursued.
2007
2007 IEEE Antennas and Propagation International Symposium
Piscataway, N.J.
IEEE
9781424408771
Donelli, Massimo; Benedetti, Manuel; Rocca, Paolo; Melgani, Farid; Massa, Andrea
File in questo prodotto:
File Dimensione Formato  
Three_dimensional_electromagnetic_sub-surface_sensing_by_means_of_a_multi-step_SVM-based_classification_technique.pdf

Solo gestori archivio

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 215.22 kB
Formato Adobe PDF
215.22 kB Adobe PDF   Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/77989
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
  • OpenAlex ND
social impact