Cost-Sensitive Rank Learning From Positive and Unlabeled Data for Visual Saliency Estimation | |
Li, Jia ; Tian, Yonghong ; Huang, Tiejun ; Gao, Wen | |
刊名 | ieee signal processing letters
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2010 | |
关键词 | Cost-sensitive positive and unlabeled data rank learning visual saliency ATTENTION |
DOI | 10.1109/LSP.2010.2048049 |
英文摘要 | This paper presents a cost-sensitive rank learning approach for visual saliency estimation. This approach avoids the explicit selection of positive and negative samples, which is often used by existing learning-based visual saliency estimation approaches. Instead, both the positive and unlabeled data are directly integrated into a rank learning framework in a cost-sensitive manner. Compared with existing approaches, the rank learning framework can take the influences of both the local visual attributes and the pair-wise contexts into account simultaneously. Experimental results show that our algorithm outperforms several state-of-the-art approaches remarkably in visual saliency estimation.; Engineering, Electrical & Electronic; SCI(E); EI; 2; ARTICLE; 6; 591-594; 17 |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.pku.edu.cn/handle/20.500.11897/243702] ![]() |
专题 | 信息科学技术学院 |
推荐引用方式 GB/T 7714 | Li, Jia,Tian, Yonghong,Huang, Tiejun,et al. Cost-Sensitive Rank Learning From Positive and Unlabeled Data for Visual Saliency Estimation[J]. ieee signal processing letters,2010. |
APA | Li, Jia,Tian, Yonghong,Huang, Tiejun,&Gao, Wen.(2010).Cost-Sensitive Rank Learning From Positive and Unlabeled Data for Visual Saliency Estimation.ieee signal processing letters. |
MLA | Li, Jia,et al."Cost-Sensitive Rank Learning From Positive and Unlabeled Data for Visual Saliency Estimation".ieee signal processing letters (2010). |
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