%0 Generic
%A Bermani, Emanuela
%A Boni, Andrea
%A Caorsi, Salvatore
%A Donelli, Massimo
%A Massa, Andrea
%D 2004
%F elediasc12:409
%T A Multi-Source Strategy based on a Learning-by-Examples Technique for Buried Object Detection
%U http://www.eledia.org/students-reports/409/
%X 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.