Classification of wooden boards by neural networks and fuzzy rules

Author

de Franca, C.A. ; Gonzaga, Adilson ; Slaets, Annie France Frere

Author_Institution

Inst. de Fisica de Sao Carlos, Brazil

fYear

1996

fDate

9-11 Dec 1996

Firstpage

190

Lastpage

195

Abstract

Fuzzy-neural systems have been applied to many engineering tasks. Fuzzy neurons in pattern classification are extremely useful because they provide a degree of membership information instead of numerical critic values such as “0” (bad) or “1” (good). This paper describes a neural network application for automatic classification of wooden boards. The basic processing unit consists of two types of generic OR and AND neurons structured in a four layer topology

Keywords

automatic optical inspection; fuzzy logic; fuzzy neural nets; fuzzy set theory; image classification; wood processing; automatic classification; degree of membership information; four layer topology; fuzzy rules; fuzzy-neural systems; neural networks; pattern classification; wooden boards; Artificial neural networks; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Manufacturing processes; Network topology; Neural networks; Neurons; Pattern recognition; Pulp manufacturing;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetic Vision, 1996. Proceedings., Second Workshop on

Conference_Location

Sao Carlos

Print_ISBN

0-8186-8058-X

Type

conf

DOI

10.1109/CYBVIS.1996.629462

Filename

629462

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3243095