?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.relation=http%3A%2F%2Fwww.eledia.org%2Fstudents-reports%2F575%2F&rft.title=An+Innovative+Real-Time+Technique+for+Buried+Object+Detection&rft.creator=Bermani%2C+Emanuela&rft.creator=Boni%2C+Andrea&rft.creator=Caorsi%2C+Salvatore&rft.creator=Massa%2C+Andrea&rft.subject=TU+Technical+Reports+and+Publications&rft.description=In+this+paper%2C+a+new+on-line+inverse+scattering+methodology+is+proposed.+The+original+problem+is+recast+into+a+regression+estimation+one+and+successively+solved+by+means+of+a+support+vector+machine+(SVM).+Although+the+approach+can+be+applied+to+various+inverse+scattering+applications%2C+it+results+very+suitable+to+deal+with+the+buried+object+detection.+The+application+of+SVMs+to+the+solution+of+such+kind+of+problems+is+firstly+illustrated.+Then%2C+some+examples%2C+concerning+the+localization+of+a+given+object+from+scattered+field+data+acquired+at+a+number+of+measurement+points%2C+are+presented.+The+effectiveness+of+the+SVM+method+is+evaluated+also+in+comparison+with+classical+neural+networks+(NNs)+based+approaches.+(c)+2003+IEEE.+Personal+use+of+this+material+is+permitted.+Permission+from+IEEE+must+be+obtained+for+all+other+users%2C+including+reprinting%2F+republishing+this+material+for+advertising+or+promotional+purposes%2C+creating+new+collective+works+for+resale+or+redistribution+to+servers+or+lists%2C+or+reuse+of+any+copyrighted+components+of+this+work+in+other+works.&rft.date=2003-04&rft.type=Technical+Report&rft.type=PeerReviewed&rft.format=text&rft.language=en&rft.identifier=http%3A%2F%2Fwww.eledia.org%2Fstudents-reports%2F575%2F1%2FDISI-11-012.R51.pdf&rft.identifier=++Bermani%2C+Emanuela+and+Boni%2C+Andrea+and+Caorsi%2C+Salvatore+and+Massa%2C+Andrea++(2003)+An+Innovative+Real-Time+Technique+for+Buried+Object+Detection.++%5BTechnical+Report%5D+++++