This review paper evaluates the potential of hyperspectral remote sensing for assessing
species diversity in homogeneous (non-tropical) and heterogeneous (tropical) forest, an …

A unified, coherent treatment of current classifier ensemble methods, from fundamentals of
pattern recognition to ensemble feature selection, now in its second edition The art and …

Diversity among the members of a team of classifiers is deemed to be a key issue in
classifier combination. However, measuring diversity is not straightforward because there is …

Multiple classifier fusion may generate more accurate classification than each of the
constituent classifiers. Fusion is often based on fixed combination rules like the product and …

Locating the center of the eyes allows for valuable information to be captured and used in a
wide range of applications. Accurate eye center location can be determined using …

Unintentional modulations of the electromagnetic signal of radio-frequency (RF) emitters are
used to identify individual sources of signals as unique from emitters of the same type in a …

This study looks at the relationships between different methods of classifier combination and
different measures of diversity. We considered 10 combination methods and 10 measures of …

The definition and modeling of customer loyalty have been central issues in customer
relationship management since many years. Recent papers propose solutions to detect …

One class classification is a binary classification task for which only one class of samples is
available for learning. In some preliminary works, we have proposed One Class Random …

One-class classification (OCC) builds models using only the samples from one class (the
target class) so as to predict whether a new-coming sample belongs to the target class or …