86 search results - page 5 / 18 » Clustering and Feature Selection using Sparse Principal Comp... |
ICMCS
2005
IEEE
14 years 1 months ago
2005
IEEE
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
ICCV
1995
IEEE
13 years 11 months ago
1995
IEEE
A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...
BMCBI
2010
13 years 7 months ago
2010
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
ISNN
2005
Springer
14 years 1 months ago
2005
Springer
Abstract. Aiming at vehicle tracking with a single moving camera for autonomous driving, this paper presents a strategy of online feature selection combined with related process fr...
ICASSP
2008
IEEE
14 years 1 months ago
2008
IEEE
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...