Cart (Loading....) | Create Account
Close category search window
 

An innovative real-time technique for buried object detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Bermani, E. ; Dept. of Inf. & Commun. Technol., Univ. of Trento, Italy ; Boni, A. ; Caorsi, S. ; Massa, A.

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.

Published in:

Geoscience and Remote Sensing, IEEE Transactions on  (Volume:41 ,  Issue: 4 )

Date of Publication:

April 2003

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.