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» Learning to rank for content-based image retrieval
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WWW
2011
ACM
13 years 2 months ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
MM
2009
ACM
221views Multimedia» more  MM 2009»
14 years 1 months ago
Using large-scale web data to facilitate textual query based retrieval of consumer photos
The rapid popularization of digital cameras and mobile phone cameras has lead to an explosive growth of consumer photo collections. In this paper, we present a (quasi) real-time t...
Yiming Liu, Dong Xu, Ivor W. Tsang, Jiebo Luo
GECCO
2008
Springer
239views Optimization» more  GECCO 2008»
13 years 8 months ago
Multiobjective design of operators that detect points of interest in images
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...
Leonardo Trujillo, Gustavo Olague, Evelyne Lutton,...
DICTA
2003
13 years 8 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang
WWW
2009
ACM
14 years 8 months ago
Learning consensus opinion: mining data from a labeling game
We consider the problem of identifying the consensus ranking for the results of a query, given preferences among those results from a set of individual users. Once consensus ranki...
Paul N. Bennett, David Maxwell Chickering, Anton M...