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» Optimizing Learning in Image Retrieval
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ICMCS
2005
IEEE
108views Multimedia» more  ICMCS 2005»
15 years 8 months ago
Analysis and Retrieval of Paintings Using Artistic Color Concepts
Traditionally artistic color concepts play an important role in the analysis of artworks, and provide valuable domain knowledge to guide the analysis and accurate retrieval of pai...
Yelizaveta Marchenko, Tat-Seng Chua, Irina Aristar...
WWW
2008
ACM
16 years 3 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
139
Voted
CVPR
2005
IEEE
16 years 4 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 4 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
119
Voted
IDA
2009
Springer
15 years 9 months ago
Estimating Markov Random Field Potentials for Natural Images
Markov Random Field (MRF) models with potentials learned from the data have recently received attention for learning the low-level structure of natural images. A MRF provides a pri...
Urs Köster, Jussi T. Lindgren, Aapo Hyvä...