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Content-based image retrieval model based on cost sensitive learning

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成果类型:
期刊论文
作者:
Jin, Cong*;Jin, Shu-Wei
通讯作者:
Jin, Cong
作者机构:
[Jin, Cong] Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.
[Jin, Shu-Wei] Ecole Normale Super, Dept Phys, 24 Rue Lhomond, F-75231 Paris 5, France.
通讯机构:
[Jin, Cong] C
Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
Content-based image retrieval;Distance metric learning;Cost sensitive learning;Classification performance;Misclassification cost;Class imbalance
期刊:
Journal of Visual Communication and Image Representation
ISSN:
1047-3203
年:
2018
卷:
55
期:
Aug.
页码:
720-728
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
How to retrieve the desired images quickly and accurately from the large scale image database has become a hot topic in the field of multimedia research. Many content-based image retrieval (CBIR) technologies already exist, but they are not always satisfactory. In many applications, the CBIR model based on machine learning relies heavily on the distance metric between samples. Although the traditional distance metric methods are simple and convenient, it is not always appropriate for CBIR tasks. In this paper, a novel distance metric learning (DML) method based on cost sensitive learning (CSL)...

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