Face recognition by concept formation neural structure

Yosuke Koyanaka, Noriyasu Homma, Masao Sakai, Kenichi Abe

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, we develop a new neural model that deals with continuation value of inputs for some practical applications of pattern recognition task. An essential core of the model is use of a novel vector representation of a target concept in a multi-level informational hierarchy that makes the model possess category formation ability from incomplete observation of the target. Simulation results demonstrate the usefulness of the model for a facial image recognition task, even if it is carried out under an incremental and unsupervised learning environment.

本文言語English
ホスト出版物のタイトルProceedings of the SICE Annual Conference
ページ1483-1487
ページ数5
出版ステータスPublished - 2004
イベントSICE Annual Conference 2004 - Sapporo, Japan
継続期間: 2004 8月 42004 8月 6

Other

OtherSICE Annual Conference 2004
国/地域Japan
CitySapporo
Period04/8/404/8/6

ASJC Scopus subject areas

  • 工学(全般)

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