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» Semi-supervised boosting using visual similarity learning
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MVA
2010
181views Computer Vision» more  MVA 2010»
13 years 6 months ago
Human action detection via boosted local motion histograms
This paper presents a novel learning method for human action detection in video sequences. The detecting problem is not limited in controlled settings like stationary background or...
Qingshan Luo, Xiaodong Kong, Guihua Zeng, Jianping...
ICDM
2002
IEEE
152views Data Mining» more  ICDM 2002»
14 years 15 days ago
Concept Tree Based Clustering Visualization with Shaded Similarity Matrices
One of the problems with existing clustering methods is that the interpretation of clusters may be difficult. Two different approaches have been used to solve this problem: conce...
Jun Wang, Bei Yu, Les Gasser
CVPR
2000
IEEE
14 years 9 months ago
Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian Networks
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...
CVPR
2006
IEEE
14 years 1 months ago
Satellite Features for the Classification of Visually Similar Classes
We show that the discrimination between visually similar classes often depends on the detection of socalled ‘satellite features’. These are local features which are not inform...
Boris Epshtein, Shimon Ullman
BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy