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".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 Bag-of-Feature 이미지 분류의 성능을 향상시키기 위한 결합된 특징 추출 방법을 제시합니다. 시각적 단어의 전역/지역 통계에 10가지 관련 연산을 적용합니다. 시각적 단어의 쌍별 조합이 크기 때문에 피셔 판별 기준 및 L1-SVM을 포함한 특징 선택 방법을 적용합니다. 제안한 방법의 유효성은 실험을 통해 확인된다.
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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},}
부
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 -