In this paper, a framework for the analysis of the error-reject trade-off in linearly combined classifiers is proposed. We start from a framework developed by Tumer and Ghosh [1,2...
The use of artificial outputs generated by a classifier simulator has recently emerged as a new trend to provide an underlying evaluation of classifier combination methods. In thi...
For combining classifiers at measurement level, the diverse outputs of classifiers should be transformed to uniform measures that represent the confidence of decision, hopefully, ...
Information fusion has, in the form of multiple classifier systems, long been a successful tool in pattern recognition applications. It is also becoming increasingly popular in bio...
Torsten Rohlfing, Adolf Pfefferbaum, Edith V. Sull...