The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Cet article présente une méthode d'extraction de caractéristiques combinée pour améliorer les performances de la classification d'images par sac de caractéristiques. Nous appliquons 10 opérations pertinentes aux statistiques globales/locales des mots visuels. Étant donné que la combinaison par paire de mots visuels est importante, nous appliquons des méthodes de sélection de caractéristiques, notamment le critère discriminant de Fisher et L1-SVM. L'efficacité de la méthode proposée est confirmée par l'expérimentation.
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Tetsu MATSUKAWA, Takio KURITA, "Extraction of Combined Features from Global/Local Statistics of Visual Words Using Relevant Operations" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 10, pp. 2870-2874, October 2010, doi: 10.1587/transinf.E93.D.2870.
Abstract: This paper presents a combined feature extraction method to improve the performance of bag-of-features image classification. We apply 10 relevant operations to global/local statistics of visual words. Because the pairwise combination of visual words is large, we apply feature selection methods including fisher discriminant criterion and L1-SVM. The effectiveness of the proposed method is confirmed through the experiment.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2870/_p
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@ARTICLE{e93-d_10_2870,
author={Tetsu MATSUKAWA, Takio KURITA, },
journal={IEICE TRANSACTIONS on Information},
title={Extraction of Combined Features from Global/Local Statistics of Visual Words Using Relevant Operations},
year={2010},
volume={E93-D},
number={10},
pages={2870-2874},
abstract={This paper presents a combined feature extraction method to improve the performance of bag-of-features image classification. We apply 10 relevant operations to global/local statistics of visual words. Because the pairwise combination of visual words is large, we apply feature selection methods including fisher discriminant criterion and L1-SVM. The effectiveness of the proposed method is confirmed through the experiment.},
keywords={},
doi={10.1587/transinf.E93.D.2870},
ISSN={1745-1361},
month={October},}
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TY - JOUR
TI - Extraction of Combined Features from Global/Local Statistics of Visual Words Using Relevant Operations
T2 - IEICE TRANSACTIONS on Information
SP - 2870
EP - 2874
AU - Tetsu MATSUKAWA
AU - Takio KURITA
PY - 2010
DO - 10.1587/transinf.E93.D.2870
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2010
AB - This paper presents a combined feature extraction method to improve the performance of bag-of-features image classification. We apply 10 relevant operations to global/local statistics of visual words. Because the pairwise combination of visual words is large, we apply feature selection methods including fisher discriminant criterion and L1-SVM. The effectiveness of the proposed method is confirmed through the experiment.
ER -