This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Abstract. We deal with two important problems in pattern recognition that arise in the analysis of large datasets. While most feature subset selection methods use statistical techn...
Feature selection is a problem of choosing a subset of relevant features. Researchers have been searching for optimal feature selection methods. `Branch and Bound' and Focus a...
— We propose a feature selection criterion based on kernel discriminant analysis (KDA) for an -class problem, which finds eigenvectors on which the projected class data are loca...
A frequent problem in density level-set estimation is the choice of the right features that give rise to compact and concise representations of the observed data. We present an e...