The combination of different experts is largely used to improve the performance of a pattern recognition system. In the case of experts whose output is a similarity score, different methods had been developed. In this paper, the combination is performed by building a similarity score space made up of the scores produced by the experts, and training a classifier into it. Different techniques based on the use of classifiers trained on the similarity score space are proposed and compared. In particular, they are used in the framework of Dynamic Score Selection mechanisms, recently proposed by the authors. Reported results on two biometric datasets show the effectiveness of the proposed approac
This paper presents two methods for calculating competence of a classifier in the feature space. The...
A useful strategy to deal with complex classification scenarios is the “divide and conquer ” approac...
This paper addresses the problem of multiclassifier system evaluation by artificially generated cl...
The combination of experts is used to improve the performance of a classification system. In this pa...
In two-class score-based problems the combination of scores from an ensemble of experts is generally...
In the biometric field, different experts are combined to improve the system reliability, as in many...
The evaluation of combination methods for multi-classifier systems is a difficult problem. In many c...
In two-class problems, the combination of the outputs (scores) of an ensemble of classifiers is wide...
In this thesis the problem of the combination of binary classifiers ensamble is faced. For each patt...
This paper presents a framework for the analysis of similarity among abstract-level classifiers and ...
An "expert" for biometric authentication systems is made up of three components: a biometric sensor,...
A biometric system for user authentication produces a matching score representing the degree of simi...
The paper discusses a problem of combination recognition scores for different classes produced by on...
AbstractThere are various machine learning algorithms for extracting patterns from data; but recentl...
In this work, we present a novel trained method for combining biometric matchers at the score level....
This paper presents two methods for calculating competence of a classifier in the feature space. The...
A useful strategy to deal with complex classification scenarios is the “divide and conquer ” approac...
This paper addresses the problem of multiclassifier system evaluation by artificially generated cl...
The combination of experts is used to improve the performance of a classification system. In this pa...
In two-class score-based problems the combination of scores from an ensemble of experts is generally...
In the biometric field, different experts are combined to improve the system reliability, as in many...
The evaluation of combination methods for multi-classifier systems is a difficult problem. In many c...
In two-class problems, the combination of the outputs (scores) of an ensemble of classifiers is wide...
In this thesis the problem of the combination of binary classifiers ensamble is faced. For each patt...
This paper presents a framework for the analysis of similarity among abstract-level classifiers and ...
An "expert" for biometric authentication systems is made up of three components: a biometric sensor,...
A biometric system for user authentication produces a matching score representing the degree of simi...
The paper discusses a problem of combination recognition scores for different classes produced by on...
AbstractThere are various machine learning algorithms for extracting patterns from data; but recentl...
In this work, we present a novel trained method for combining biometric matchers at the score level....
This paper presents two methods for calculating competence of a classifier in the feature space. The...
A useful strategy to deal with complex classification scenarios is the “divide and conquer ” approac...
This paper addresses the problem of multiclassifier system evaluation by artificially generated cl...