In the paper, an approach to the automatic design of multiple classifier systems is proposed. Given an initial large set of classifiers, our approach is aimed ...

Multiple classifier systems based on the combination of outputs of a set of different classifiers have been proposed as a method for the development of high ...

Design of Effective Multiple Classifier Systems by Clustering of Classifiers ICPR, 2000. ICPR v2 2000 · DBLP · Scholar · DOI. Full names. Links ISxN. @ ...

Design of effective multiple classifier systems by clustering of classifiers. GIACINTO, GIORGIO;ROLI, FABIO;FUMERA, GIORGIO. 2000-01-01. Abstract. In the field ...

27 We used a method of choice based on a clustering algorithm, grouping the classifiers on the basis of the Q t diversity metric, i.e. by Eq. (3.1) and ...

In this paper, an approach to the automatic design of multiple classifier systems is proposed. Given an initial large set of classifiers, our approach is aimed ...

Reported results on the classification of multisensor remote-sensing images show that this approach allows the design of effective multiple classifier systems.

Design of effective multiple classifier systems by clustering of classifiers · Design of effective neural network ensembles for image classification purposes.

In the field of pattern recognition, multiple classifier systems based on the combination of outputs of a set of different classifiers have been proposed as ...

Oct 4, 2021 · The Multiple Classifier System (or classifier ensemble) is the consensus of different clustering algorithms that can provide high accuracy for the best ...