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...
In this paper, the error-reject trade-off of linearly combined multiple classifiers is analysed in the framework of the minimum risk theory. Theoretical analysis described in [12,1...
So far few theoretical works investigated the conditions under which specific fusion rules can work well, and a unifying framework for comparing rules of different complexity is cl...
We investigate in this paper the combination of DBN (Dynamic Bayesian Network) classifiers, either independent or coupled, for the recognition of degraded characters. The independ...