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A new online inverse scattering methodology is proposed. The original problem is recast into a regression estimation and successively solved by means of a support vector machine (SVM). Although the approach can be applied to various inverse scattering applications, it is very suitable for dealing with buried object detection. The application of SVMs to the solution of such problems is firstly illustrated. Then some examples, concerning the localization of a given object from scattered field data acquired at a number of measurement points, are presented. The effectiveness of the SVM method is evaluated in comparison with classical neural network based approaches.