CAS OpenIR  > 中科院上海应用物理研究所2011-2019年
Ambiguous Proximity Distribution
Wang, QQ; Li, YP; wangquanquan@sinap.ac.cn; ypli@sinap.ac.cn
2014
Conference Name10th International Conference on Intelligent Computing (ICIC)
Source PublicationINTELLIGENT COMPUTING METHODOLOGIES
Pages409—421
Conference Date2014
Conference PlaceTaiyuan, PEOPLES R CHINA
PublisherSPRINGER-VERLAG BERLIN
AbstractProximity Distribution Kernel is an effective method for bag-of-featues based image representation. In this paper, we investigate the soft assignment of visual words to image features for proximity distribution. Visual word contribution function is proposed to model ambiguous proximity distributions. Three ambiguous proximity distributions is developed by three ambiguous contribution functions. The experiments are conducted on both classification and retrieval of medical image data sets. The results show that the performance of the proposed methods, Proximity Distribution Kernel (PDK), is better or comparable to the state-of-the-art bag-of-features based image representation methods.
ISSN0302-9743
ISBN978-3-319-09339-0; 978-3-319-09338-3
Indexed BySCI
Language英语
Document Type会议论文
Identifierhttp://ir.sinap.ac.cn/handle/331007/14735
Collection中科院上海应用物理研究所2011-2019年
Corresponding Authorwangquanquan@sinap.ac.cn; ypli@sinap.ac.cn
Recommended Citation
GB/T 7714
Wang, QQ,Li, YP,wangquanquan@sinap.ac.cn,et al. Ambiguous Proximity Distribution[C]:SPRINGER-VERLAG BERLIN,2014:409—421.
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