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) |
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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: | https://repo.uum.edu.my/id/eprint/15518 |
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