Clustering algorithms are increasingly employed for the categorization of image databases, in order to provide users with database overviews and make their access more effective. ...
It is generally believed that quadratic discriminant analysis (QDA) can better fit the data in practical pattern recognition applications compared to linear discriminant analysis ...
Jie Wang, Konstantinos N. Plataniotis, Juwei Lu, A...
Feature selection is an important preprocessing step in mining high-dimensional data. Generally, supervised feature selection methods with supervision information are superior to ...
In this paper, we present a method for binary image comparison. For binary images, intensity information is poor and shape extraction is often difficult. Therefore binary images h...
Our goal is to design algorithms that give a linearity measure for planar point sets. There is no explicit discussion on linearity in literature, although some existing shape meas...
The spectrum of a graph has been widely used in graph theory to characterise the properties of a graph and extract information from its structure. It has also been employed as a g...
Prototype selection problem consists of reducing the size of databases by removing samples that are considered noisy or not influential on nearest neighbour classification tasks. ...
A maximum-entropy approach to generative similarity-based classifiers model is proposed. First, a descriptive set of similarity statistics is assumed to be sufficient for classifi...
Video object (VO) extraction is of great importance in multimedia processing. In recent years approaches have been proposed to deal with VO extraction as a classification problem....