Large-scale image classification using ensembles of nested dichotomies

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Title:	Large-scale image classification using ensembles of nested dichotomies
Author:	Ramisa Ayats, Arnau; Torras, Carme
Other authors:	Institut de Robòtica i Informàtica Industrial; Universitat Politècnica de Catalunya. ROBiri - Grup de Robòtica de l'IRI
Abstract:	Many techniques to reduce the cost at test time in large-scale problems involve a hierarchical organization of classifiers, but are either too expensive to learn or degrade the classification performance. Conversely, in this work we show that using ensembles of randomized hierarchical decompositions of the original problem can both improve the accuracy and reduce the computational complexity at test time. The proposed method is evaluated in the ImageNet Large Scale Visual Recognition Challenge’10, with promising results.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Informàtica::Robòtica -Computer vision -computer vision image classification Author keywords: large-scale image classification -classifier ensembles -ensembles of nested dichotomies -Visió per ordinador -Classificació INSPEC::Pattern recognition::Computer vision
Rights:	Attribution-NonCommercial-NoDerivs 3.0 Spain http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Submitted version Conference Object
Published by:	IOS Press
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