Name
Abstract | ||
|---|---|---|
The Multiple Classifier Systemsare nowadays one of the most promising directions in pattern recognition. There are many methods of decision making by the ensemble of classifiers. The most popular are methods that have their origin in voting method, where the decision of the common classifier is a combination of individual classifiers' decisions. This work presents methods of classifier combination, where neural networks plays a role of fuser block. Fusion on level of recognizer responses or values of their discriminant functions is applied. The qualities of proposed methods are evaluated via computer experiments on generated data and two benchmark databases. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-87656-4_45 | HAIS |
Keywords | Field | DocType |
classifier response,classifier combination,comparative study,pattern recognition,neural network,fuser block,discriminant function,individual classifier,benchmark databases,computer experiment,multiple classifier systemsare,common classifier | Pattern recognition,Discriminant,Random subspace method,Computer science,Cascading classifiers,Artificial intelligence,Classifier (linguistics),Margin classifier,Artificial neural network,Machine learning,Discriminant function analysis,Quadratic classifier | Conference |
Volume | ISSN | Citations |
5271 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 18 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Wozniak | 1 | 764 | 83.90 |
| Konrad Jackowski | 2 | 136 | 10.46 |