TY  - INPR
TI  - A Multi-Source Strategy based on a Learning-by-Examples Technique for Buried Object Detection
UR  - http://www.eledia.org/students-reports/409/
Y1  - 2004/08//
N2  - 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.
ID  - elediasc12409
A1  - Bermani, Emanuela
A1  - Boni, Andrea
A1  - Caorsi, Salvatore
A1  - Donelli, Massimo
A1  - Massa, Andrea
AV  - public
ER  -