“School of Cognitive Sciences”
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| Paper IPM / Cognitive Sciences / 8806 |
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| Abstract: | |||||||||
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Recent studies in neurobiology and especially in neuroimaging report that a
gating mechanism prior to face processing levels of human visual system,
facilitates the face/nonface recognition task. In accordance to these biological
evidences, we propose a face/nonface recognition model which makes use of
mixture of experts network. In order to improve the face/nonface recognition
accuracy, the outputs of the expert networks are combined using a gating
network. A novel structure, which is the use of multilayer perceptrons (MLPs) in
forming the expert networks, is introduced. The learning algorithm is modified to
be adapted with the MLP networks. The results reveal that using a mixture of
simple MLPs is much more beneficial, in many respects, as it shows more
certainty at its output and is also easier to train than a single, but complex, MLP.
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