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ICIP
2009
IEEE
15 years 10 months ago
Object Detection Via Boosted Deformable Features
It is a common practice to model an object for detection tasks as a boosted ensemble of many models built on features of the object. In this context, features are defined as subre...
TEC
2008
146views more  TEC 2008»
14 years 9 months ago
An Evolutionary Algorithm Approach to Optimal Ensemble Classifiers for DNA Microarray Data Analysis
In general, the analysis of microarray data requires two steps: feature selection and classification. From a variety of feature selection methods and classifiers, it is difficult t...
Kyung-Joong Kim, Sung-Bae Cho
88
Voted
MCS
2010
Springer
14 years 11 months ago
Choosing Parameters for Random Subspace Ensembles for fMRI Classification
Abstract. Functional magnetic resonance imaging (fMRI) is a noninvasive and powerful method for analysis of the operational mechanisms of the brain. fMRI classification poses a sev...
Ludmila I. Kuncheva, Catrin O. Plumpton
ICANN
2003
Springer
15 years 2 months ago
Neural Network Ensemble with Negatively Correlated Features for Cancer Classification
The development of microarray technology has supplied a large volume of data to many fields. In particular, it has been applied to prediction and diagnosis of cancer, so that it ex...
Hong-Hee Won, Sung-Bae Cho
CVPR
2005
IEEE
15 years 11 months ago
Rank-R Approximation of Tensors: Using Image-as-Matrix Representation
We present a novel multilinear algebra based approach for reduced dimensionality representation of image ensembles. We treat an image as a matrix, instead of a vector as in tradit...
Hongcheng Wang, Narendra Ahuja