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» Subspace Clustering of High Dimensional Data
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DATAMINE
2007
101views more  DATAMINE 2007»
13 years 4 months ago
Using metarules to organize and group discovered association rules
The high dimensionality of massive data results in the discovery of a large number of association rules. The huge number of rules makes it difficult to interpret and react to all ...
Abdelaziz Berrado, George C. Runger
CIVR
2007
Springer
169views Image Analysis» more  CIVR 2007»
13 years 11 months ago
Whitened LDA for face recognition
Over the years, many Linear Discriminant Analysis (LDA) algorithms have been proposed for the study of high dimensional data in a large variety of problems. An intrinsic limitatio...
Vo Dinh Minh Nhat, Sungyoung Lee, Hee Yong Youn
CVIU
2007
146views more  CVIU 2007»
13 years 4 months ago
Face detection in gray scale images using locally linear embeddings
The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial ex...
Samuel Kadoury, Martin D. Levine
SIAMJO
2010
100views more  SIAMJO 2010»
12 years 11 months ago
Explicit Sensor Network Localization using Semidefinite Representations and Facial Reductions
The sensor network localization, SNL , problem in embedding dimension r, consists of locating the positions of wireless sensors, given only the distances between sensors that are ...
Nathan Krislock, Henry Wolkowicz
ICPR
2004
IEEE
14 years 5 months ago
Selecting Models from Videos for Appearance-Based Face Recognition
In this paper, we propose an unsupervised approach to select representative face samples (models) from raw videos and build an appearance-based face recognition system. The approa...
Abdenour Hadid, Matti Pietikäinen