Reference : Decision Trees and Random Subwindows for Object Recognition
Scientific congresses and symposiums : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/12608
Decision Trees and Random Subwindows for Object Recognition
English
Marée, Raphaël mailto [Université de Liège - ULg > Department of Electrical Engineering and Computer Science > Systèmes et Modélisation > >]
Geurts, Pierre mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
Piater, Justus mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > INTELSIG Group >]
Wehenkel, Louis mailto [Université de Liège - ULg > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2005
ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005)
Yes
No
International
ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005)
Bonn
Germany
[en] machine learning
[en] In this paper, we compare five tree-based machine learning methods within a recent generic image classification framework based on random extraction and classification of subwindows. We evaluate them on three publicly available object recognition datasets (COIL-100, ETH-80, and ZuBuD). Our comparison shows that this general and conceptually simple framework yields good results when combined with ensemble of decision trees, especially when using Tree Boosting or Extra-Trees. The latter is also particularly attractive in terms of computational efficiency.
Fonds de la Recherche Scientifique (Communauté française de Belgique) - F.R.S.-FNRS ; Région wallonne : Direction générale des Technologies, de la Recherche et de l'Energie - DGTRE
http://hdl.handle.net/2268/12608
http://www.montefiore.ulg.ac.be/services/stochastic/pubs/2005/MGPW05a

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