TY  - GEN
AV  - public
ID  - elediasc12364
A1  - Donelli, Massimo
A1  - Benedetti, Manuel
A1  - Rocca, Paolo
A1  - Melgani, Farid
A1  - Massa, Andrea
N2  - In this paper, the classification approach is extended from 2D to the three-dimensional(3D) case carefully addressing the increased complexity issue by means of an effective multi-step strategy. As a matter of fact, by iteratively processing the training dataset (without requiring an extra amount of measurements), the proposed method is aimed at improving the spatial resolution of the original classification technique [6] even though dealing with a more complex problem. The effectiveness of the proposed approach has been preliminary assessed through a set of numerical experiments also in correspondence with blurred data and some representative results are shown in the following. This is the author's version of the final version available at IEEE.
UR  - http://www.eledia.org/students-reports/364/
Y1  - 2011/01//
TI  - Three Dimensional Electromagnetic Sub-Surface Sensing by Means of a Multi-Step SVM-Based Classification Technique
ER  -