A Multi-Source Strategy based on a Learning-by-Examples Technique for Buried Object Detection

Bermani, Emanuela and Boni, Andrea and Caorsi, Salvatore and Donelli, Massimo and Massa, Andrea (2004) A Multi-Source Strategy based on a Learning-by-Examples Technique for Buried Object Detection. UNSPECIFIED. (In Press)

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    Abstract

    In the framework of buried object detection and subsurface sensing, some of the main difficulties in the reconstruction process are certainly due to the aspect-limited nature of available measurement data and to the requirement of an on-line reconstruction. To limit these problems, a multi-source (MS) learning-by-example (LBE) technique is proposed in this paper. In order to fully exploit the more attractive features of the MS strategy, the proposed approach is based on a support vector machine (SVM). The effectiveness of the MS-LBE technique is evaluated by comparing the achieved results with those obtained by means of a previously developed single-source (SS) SVM-based procedure for an ideal as well as a noisy enviroment.

    Item Type: Departmental Technical Report
    Department or Research center: Information Engineering and Computer Science
    Subjects: Q Science > QC Physics (General) > QC661 Electromagnetic Theory
    Q Science > QC Physics (General) > QC760 Electromagnetism
    Report Number: DIT-04-067
    Repository staff approval on: 01 Sep 2004

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