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Chapter and Conference Paper
Balance between Diversity and Relevance for Image Search Results
Image search reranking has received great attention since it overcomes the drawback of “only textual features utilization” in nowadays web-scale image search engines. Most of existing methods focus on relevanc...
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Chapter and Conference Paper
Image Search Reranking with Semi-supervised LPP and Ranking SVM
Learning to rank is one of the most popular ranking methods used in image retrieval and search reranking. However, the high-dimension of the visual features usually causes the problem of “curse of dimensionali...
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Chapter and Conference Paper
Marginal Fisher Regression Classification for Face Recognition
This paper presents a novel marginal Fisher regression classification (MFRC) method by incorporating the ideas of marginal Fisher analysis (MFA) and linear regression classification (LRC). The MFRC aims at minimi...
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Chapter and Conference Paper
Enhancement for Dust-Sand Storm Images
A novel dust-sand storm image enhancement scheme is proposed. The input degraded color image is first convert into CIELAB color space. Then two chromatic components (a* and b*) are combined to perform color cast ...