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. © Springer-Verlag Berlin Heidelberg 2009.
Cite
CITATION STYLE
Faundez-Zanuy, M. (2009). Data fusion at different levels. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5398 LNAI, pp. 94–103). https://doi.org/10.1007/978-3-642-00525-1_9
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