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ISDA
2010
IEEE
13 years 5 months ago
Feature selection is the ReliefF for multiple instance learning
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...
PRL
2008
82views more  PRL 2008»
13 years 7 months ago
Optimistic pruning for multiple instance learning
This paper introduces a simple evaluation function for multiple instance learning that admits an optimistic pruning strategy. We demonstrate comparable results to state of the art...
Amy McGovern, David Jensen
CVPR
2009
IEEE
15 years 2 months ago
Multiple Instance Feature for Robust Part-based Object Detection
Feature misalignment in object detection refers to the phenomenon that features which re up in some positive detection windows do not re up in other pos- itive detection windo...
Zhe Lin (University of Maryland at College Park), ...
ACCV
2007
Springer
14 years 1 months ago
Face Mis-alignment Analysis by Multiple-Instance Subspace
In this paper, we systematically study the effect of poorly registered faces on the training and inferring stages of traditional face recognition algorithms. We then propose a nov...
Zhiguo Li, Qingshan Liu, Dimitris N. Metaxas
CVPR
2010
IEEE
14 years 3 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...