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97
Voted
CVPR
2000
IEEE
16 years 2 months ago
Improving Visual Matching
Many visual matching algorithms can be described in terms of the features and the inter-feature distance or metric. The most commonly used metric is the sum of squared di erences ...
Michael S. Lew, Nicu Sebe, Thomas S. Huang
CVPR
2001
IEEE
16 years 2 months ago
Clustering Art
We extend a recently developed method [1] for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing in order to...
Kobus Barnard, Pinar Duygulu, David A. Forsyth
123
Voted
CVPR
2004
IEEE
16 years 2 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
CVPR
2004
IEEE
16 years 2 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
94
Voted
CVPR
2006
IEEE
16 years 2 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang