Presentation 1998/6/18
Membership Feedback for Context Propagation
Kohei INOUE, Kiichi URAHAMA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) A pattern recognition model is presented which incorporates temporal or spatial context informations by feedback of membersihp values outputted from WTA neurons at higher levels into pattern selective neurons at lower levels. An unsupervised learning algorithm is derived from the maximum likelihood estimation of prototypes of clusters. Temporal context is considered at first, and a model is examined where a classification membership at each timepoint is fed back at the next timepoint. This model is shown to partition data according to their temporal proximity rather than their proximity in feature spaces. This model is then applied to position invariant pattern recognition of simple images. Spatial context is considered next, and pattern recognition model similar to the one for temporal context is effective for spatial smoothing and disambiguation of noisy and ambiguous spatial signals.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) context dependence / membersihp feedback / position invariant pattern recognition / unsupervised learning
Paper # PRMU98-32
Date of Issue

Conference Information
Committee PRMU
Conference Date 1998/6/18(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Membership Feedback for Context Propagation
Sub Title (in English)
Keyword(1) context dependence
Keyword(2) membersihp feedback
Keyword(3) position invariant pattern recognition
Keyword(4) unsupervised learning
1st Author's Name Kohei INOUE
1st Author's Affiliation Faculty of Visual Communication Design, Kyushu Institute of Design()
2nd Author's Name Kiichi URAHAMA
2nd Author's Affiliation Faculty of Visual Communication Design, Kyushu Institute of Design
Date 1998/6/18
Paper # PRMU98-32
Volume (vol) vol.98
Number (no) 126
Page pp.pp.-
#Pages 6
Date of Issue