000145938 001__ 145938
000145938 005__ 20180913055630.0
000145938 037__ $$aCONF
000145938 245__ $$aBiometric Person Authentication IS A Multiple Classifier Problem
000145938 269__ $$a2007
000145938 260__ $$c2007
000145938 336__ $$aConference Papers
000145938 500__ $$aIDIAP-RR 07-03
000145938 520__ $$aSeveral papers have already shown the interest of using multiple classifiers in order to enhance the performance of biometric person authentication systems. In this paper, we would like to argue that the core task of Biometric Person Authentication is actually a multiple classifier problem as such: indeed, in order to reach state-of-the-art performance, we argue that all current systems , in one way or another, try to solve several tasks simultaneously and that without such joint training (or sharing), they would not succeed as well. We explain hereafter this perspective, and according to it, we propose some ways to take advantage of it, ranging from more parameter sharing to similarity learning.
000145938 700__ $$0243961$$aBengio, Samy$$g140142
000145938 700__ $$aMariéthoz, Johnny
000145938 7112_ $$a7th International Workshop on Multiple Classifier Systems, MCS
000145938 8564_ $$uhttp://publications.idiap.ch/downloads/papers/2007/bengio-mcs-2007.pdf$$zURL
000145938 8564_ $$uhttp://publications.idiap.ch/index.php/publications/showcite/bengio:rr07-03$$zRelated documents
000145938 8564_ $$s253782$$uhttps://infoscience.epfl.ch/record/145938/files/bengio-mcs-2007.pdf$$zn/a
000145938 909C0 $$0252189$$pLIDIAP$$xU10381
000145938 909CO $$ooai:infoscience.tind.io:145938$$pconf$$pSTI
000145938 937__ $$aLIDIAP-CONF-2007-005
000145938 970__ $$abengio:mcs:2007/LIDIAP
000145938 973__ $$aEPFL$$sPUBLISHED
000145938 980__ $$aCONF