Presentation 2004/11/19
A Face recognition model based on the knowledge of hippocampal circuitry
Hiroshi KAGE, Manabu HASHIMOTO, Ken-ichi TANAKA, Kazuo KYUMA,
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Abstract(in English) This paper describes a biologically-motivated face recognition model, based on neurophysiological findings related to hippocampal circuitry. Hippocampus, a part of mammal limbic system, is supposed to play a key role in some learning processes. Nakazawa's experiment shows that hippocampal CA3 neurons might be involved in some perceptual tasks such as pattern completion. It has been reported that many hippocampal neurons have activity-dependent synaptic plasticity, and that hippocampal CA3 neurons have recurrent connections. From the computational point of view, such connections can contribute to realize the property of pattern completion. We argue that such neuroscientific framework can apply to realize a very robust associative memory dealing with face images including occlusion, noise, or some partial distortion.
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Keyword(in English) hippocampal circuitry / associative memory / face recognition / pattern completion
Paper # NLP2004-71,NC2004-87
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Conference Date 2004/11/19(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A Face recognition model based on the knowledge of hippocampal circuitry
Sub Title (in English)
Keyword(1) hippocampal circuitry
Keyword(2) associative memory
Keyword(3) face recognition
Keyword(4) pattern completion
1st Author's Name Hiroshi KAGE
1st Author's Affiliation Advanced Technology R&D Center, Mitsubishi Electric Corporation()
2nd Author's Name Manabu HASHIMOTO
2nd Author's Affiliation Advanced Technology R&D Center, Mitsubishi Electric Corporation
3rd Author's Name Ken-ichi TANAKA
3rd Author's Affiliation Advanced Technology R&D Center, Mitsubishi Electric Corporation
4th Author's Name Kazuo KYUMA
4th Author's Affiliation Advanced Technology R&D Center, Mitsubishi Electric Corporation
Date 2004/11/19
Paper # NLP2004-71,NC2004-87
Volume (vol) vol.104
Number (no) 473
Page pp.pp.-
#Pages 4
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