Reference : Towards Generic Image Classification using Tree-based Learning: an Extensive Empirica...
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/2268/191267
Towards Generic Image Classification using Tree-based Learning: an Extensive Empirical Study
English
Marée, Raphaël mailto [Université de Liège > > GIGA-Research >]
Geurts, Pierre mailto [Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Algorith. des syst. en interaction avec le monde physique >]
Wehenkel, Louis mailto [Université de Liège > Dép. d'électric., électron. et informat. (Inst.Montefiore) > Systèmes et modélisation >]
2016
Pattern Recognition Letters
Elsevier Science
Yes (verified by ORBi)
International
0167-8655
[en] This paper considers the general problem of image classification
without using any prior knowledge about image classes. We study
variants of a method based on supervised learning whose common steps
are the extraction of random subwindows described by raw pixel intensity values
and the use of ensemble of extremely randomized trees to directly
classify images or to learn image features. The influence of method
parameters and variants is thoroughly evaluated so as to provide baselines and
guidelines for future studies. Detailed results are provided on 80
publicly available datasets that depict very diverse types of images
(more than 3800 image classes and over 1.5 million images).
http://hdl.handle.net/2268/191267
10.1016/j.patrec.2016.01.006
This is the author post-print (ie. final draft post-refereeing) accepted version of the paper. Publisher (Elsevier) version will be available in Pattern Recognition Letters. http://www.journals.elsevier.com/pattern-recognition-letters/

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