M. Faundez-Zanuy. Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers, Springer Berlin Heidelberg, (2009)
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.
Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers
%0 Book Section
%1 faundezzanuy2009fusion
%A Faundez-Zanuy, Marcos
%B Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers
%C Springer Berlin Heidelberg
%D 2009
%E Esposito, Anna
%E Hussain, Amir
%E Marinaro, Maria
%E Martone, Raffaele
%K data fusion integration multimodal sensor
%P 94-103
%T Data Fusion at Different Levels
%U http://dx.doi.org/10.1007/978-3-642-00525-1_9
%X 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.
%@ 978-3-642-00525-1
@incollection{faundezzanuy2009fusion,
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.},
added-at = {2016-02-10T12:34:43.000+0100},
address = {Springer Berlin Heidelberg},
author = {Faundez-Zanuy, Marcos},
biburl = {https://www.bibsonomy.org/bibtex/23ac0a13dec248bb99833194084e70a19/porta},
booktitle = {Multimodal Signals: Cognitive and Algorithmic Issues: COST Action 2102 and euCognition International School Vietri sul Mare, Italy, April 21-26, 2008 Revised Selected and Invited Papers},
editor = {Esposito, Anna and Hussain, Amir and Marinaro, Maria and Martone, Raffaele},
howpublished = {Berlin, Heidelberg},
interhash = {3deef4f821353583b2714a725f3fbffd},
intrahash = {3ac0a13dec248bb99833194084e70a19},
isbn = {978-3-642-00525-1},
keywords = {data fusion integration multimodal sensor},
pages = {94-103},
timestamp = {2016-02-10T12:40:07.000+0100},
title = {Data Fusion at Different Levels},
url = {http://dx.doi.org/10.1007/978-3-642-00525-1_9},
year = 2009
}