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Face-voice association towards multimodal-based authentication using modulated spike-time dependent learning


Yusoff, Nooraini and Ibrahim, Mohammed Fadhil (2015) Face-voice association towards multimodal-based authentication using modulated spike-time dependent learning. In: 5th International Conference on Computing and Informatics (ICOCI) 2015, 11-13 August 2015, Istanbul, Turkey.

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Abstract

We propose a reward based learning to associate face and voice stimuli. In particular, we implement learning in a spiking neural network paradigm using modulated spike-time dependent plasticity (STDP).The face and voice stimuli are paired with a temporal delay, and the network is trained to associate the paired face-voice with a target response.The learning rule is dependent on a reward policy in which the network is given a positive reward for a correct response to a face-voice stimulus pair, or the network receives a negative reward for an incorrect response. Despite a stochastic environment, the learning result of real images and sound indicates a good performance with 77.33% accuracy.The result demonstrates that a machine can be trained to associate a pair of biometric inputs to a target response.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN No: 978-967-0910-02-4 Jointly organized by: Universiti Utara Malaysia (UUM) & Istanbul Sabahattin Zaim University (IZU)
Uncontrolled Keywords: multimodal, associative learning, spiking neural network, spiketime dependent plasticity
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Computing
Depositing User: Dr. Nooraini Yusoff
Date Deposited: 30 Sep 2015 06:56
Last Modified: 28 Apr 2016 01:58
URI: http://repo.uum.edu.my/id/eprint/15518

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