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This paper presents four schemes for soft fusion of the outputs of multiple classi®ers. In the ®rst three approaches, the weights assigned to the classi®ers or groups of them are data dependent. The ®rst approach involves the calculation of fuzzy integrals. The second scheme performs weighted averaging with data-dependent weights. The third approach(More)
The long-term goal of the work is a decision support system for diagnostics of laryngeal diseases. Colour images of vocal folds, a voice signal, and questionnaire data are the information sources to be used in the analysis. This paper is concerned with automated analysis of a voice signal applied to screening of laryngeal diseases. The effectiveness of 11(More)
Aggregating outputs of multiple classifiers into a committee decision is one of the most important techniques for improving classification accuracy. The issue of selecting an optimal subset of relevant features plays also an important role in successful design of a pattern recognition system. In this paper, we present a neural network based approach for(More)
OBJECTIVE The objective of this work is to investigate a possibility of creating a computer-aided decision support system for an automated analysis of vocal cord images aiming to categorize diseases of vocal cords. METHODOLOGY The problem is treated as a pattern recognition task. To obtain a concise and informative representation of a vocal cord image,(More)