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» Learning Distance Functions for Image Retrieval
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KDD
2006
ACM
213views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 1 months ago
Formulating context-dependent similarity functions
Tasks of information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be formulated in a con...
Gang Wu, Edward Y. Chang, Navneet Panda
ICPR
2000
IEEE
14 years 8 months ago
Image Distance Using Hidden Markov Models
We describe a method for learning statistical models of images using a second-order hidden Markov mesh model. First, an image can be segmented in a way that best matches its stati...
Daniel DeMenthon, David S. Doermann, Marc Vuilleum...
NIPS
2004
13 years 8 months ago
Instance-Based Relevance Feedback for Image Retrieval
High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of t...
Giorgio Giacinto, Fabio Roli
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 12 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang