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ICML
2009
IEEE
14 years 8 months ago
Learning instance specific distances using metric propagation
In many real-world applications, such as image retrieval, it would be natural to measure the distances from one instance to others using instance specific distance which captures ...
De-Chuan Zhan, Ming Li, Yu-Feng Li, Zhi-Hua Zhou
PR
2006
164views more  PR 2006»
13 years 7 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
PR
2006
141views more  PR 2006»
13 years 7 months ago
Relaxational metric adaptation and its application to semi-supervised clustering and content-based image retrieval
The performance of many supervised and unsupervised learning algorithms is very sensitive to the choice of an appropriate distance metric. Previous work in metric learning and ada...
Hong Chang, Dit-Yan Yeung, William K. Cheung
SIGIR
2008
ACM
13 years 7 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang
CVPR
2001
IEEE
14 years 9 months ago
Learning Similarity Measure for Natural Image Retrieval with Relevance Feedback
A new scheme of learning similarity measure is proposed for content-based image retrieval (CBIR). It learns a boundary that separates the images in the database into two parts. Im...
Guodong Guo, Anil K. Jain, Wei-Ying Ma, HongJiang ...