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Decision Trees and Random Subwindows for Object Recognition
Marée, Raphaël; Geurts, Pierre; Piater, Justus et al.
2005In ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005)
Peer reviewed
 

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Keywords :
machine learning
Abstract :
[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.
Disciplines :
Computer science
Author, co-author :
Marée, Raphaël  ;  Université de Liège - ULiège > Department of Electrical Engineering and Computer Science > Systèmes et Modélisation
Geurts, Pierre  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Piater, Justus ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > INTELSIG Group
Wehenkel, Louis  ;  Université de Liège - ULiège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation
Language :
English
Title :
Decision Trees and Random Subwindows for Object Recognition
Publication date :
2005
Event name :
ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005)
Event place :
Bonn, Germany
Audience :
International
Main work title :
ICML workshop on Machine Learning Techniques for Processing Multimedia Content (MLMM2005)
Peer reviewed :
Peer reviewed
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique
DGTRE - Région wallonne. Direction générale des Technologies, de la Recherche et de l'Énergie
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