Reference : Robust Automatic Target Recognition Using Extra-trees
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/2268/103113
Robust Automatic Target Recognition Using Extra-trees
English
Pisane, Jonathan mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images >]
Marée, Raphaël mailto [Université de Liège - ULg > > GIGA-Management : Plateforme bioinformatique >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Verly, Jacques mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Exploitation des signaux et images >]
2010
Robust Automatic Target Recognition Using Extra-trees
Pisane, Jonathan mailto
IEEE
Yes
No
International
International Radar Conference
from 10-05-2010 to 14-05-2010
IEEE
Washington D.C.
USA
[en] Extra-trees ; MSTAR ; ATR
[en] In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT image classifier. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees). This approach requires very little pre-processing of the images, thereby limiting the computational load. It was successfully tested on an extended version of the public standard MSTAR database, that includes targets of interest, false targets, and background clutter. A misclassification rate of about three percent has been achieved.
INTELSIG - EECS
Fonds pour la formation à la Recherche dans l'Industrie et dans l'Agriculture (Communauté française de Belgique) - FRIA
Researchers ; Professionals ; Students ; Others
http://hdl.handle.net/2268/103113

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