Home » conference programme » Innovative Production Machines and Systems » Identifying defects on plywood using a minimum distance classifier and a neural network

Introduction

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 Introduction

  • Two types of classifiers considered

  • The minimum distance classifier

    • a relatively simple classifier

  • The neural network

    • an intelligent classifier

  • The application considered

    • identifying defects on plywood

  • Wood veneer inspection minimum distance classifier (WVIMDC)

  • Wood veneer inspection neural network (WVINN)

‹ ContentsupA generic Classifier ›
 In this paper a two types of classifiers are considered for identifying defects on plywood. The MDC is an example of a relatively simple classifier and a NN is an example of an intelligent classifier. The performance of the two classifiers are compared, namely, WNIMDC and WVINN.

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