Pattern recognition by neural-network processing in the combined spatial-orientational space

H. Greenspan, M. Fleisher, M. Porat, Y. Y. Zeevi

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

A dual stage neural-network architecture is proposed, for the combined local and global processing of visual dot-patterns, in the spatial-orientational space. Dipoles defining local orientation are first determined by a Hopfield-type network. The second stage, consisting of a layered neural network, is then trained by the back propagation algorithm with a new cost function to discriminate between dipole patterns. The network performance in classification tasks is similar to that of human vision.

Original languageEnglish
DOIs
StatePublished - 1989
Externally publishedYes
Event16th Conference of Electrical and Electronics Engineers in Israel, EEIS 1989 - Tel-Aviv, Israel
Duration: 7 Mar 19899 Mar 1989

Conference

Conference16th Conference of Electrical and Electronics Engineers in Israel, EEIS 1989
Country/TerritoryIsrael
CityTel-Aviv
Period7/03/899/03/89

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