Data Fusion at Different Levels

Authors:
Marcos Faundez-Zanuy
Affiliations:
Escola Universitària Politècnica de Mataró, MATARÓ (BARCELONA), 08303
Venue:
Multimodal Signals: Cognitive and Algorithmic Issues
Year:
2009

Citing 4
Cited 1

Logical versus analogical or symbolic versus connectionist or neat versus scruffy

AI Magazine
Decision Combination in Multiple Classifier Systems

IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of Multibiometrics (International Series on Biometrics)

Handbook of Multibiometrics (International Series on Biometrics)
Maximum likelihood linear programming data fusion for speaker recognition

Speech Communication

Emotional vocal expressions recognition using the COST 2102 italian database of emotional speech

COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper summarizes the main characteristics of data fusion at different levels (sensor, features, scores and decisions). Although it is presented in the framework of biometric applications it is general for all the pattern recognition applications because this presentation is focused in the main blocks of a general pattern recognition system. Thus, the application in mind will imply a different sensor, feature extractor, classifier and decision maker but data fusion will be performed in a similar way.