<efrbr:recordSet xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:efrbr="http://vfrbr.info/efrbr/1.1" xmlns:efrbr-work="http://vfrbr.info/efrbr/1.1/work" xmlns:efrbr-expression="http://vfrbr.info/efrbr/1.1/expression" xmlns:efrbr-manifestation="http://vfrbr.info/efrbr/1.1/manifestation" xmlns:efrbr-person="http://vfrbr.info/efrbr/1.1/person" xmlns:efrbr-corporateBody="http://vfrbr.info/efrbr/1.1/corporateBody" xmlns:efrbr-concept="http://vfrbr.info/efrbr/1.1/concept" xmlns:efrbr-structure="http://vfrbr.info/efrbr/1.1/structure" xmlns:efrbr-responsible="http://vfrbr.info/efrbr/1.1/responsible" xmlns:efrbr-subject="http://vfrbr.info/efrbr/1.1/subject" xmlns:efrbr-other="http://vfrbr.info/efrbr/1.1/other" xsi:schemaLocation="http://vfrbr.info/efrbr/1.1 http://vfrbr.info/schemas/1.1/efrbr.xsd"><efrbr:entities><efrbr-work:work identifier="http://purl.tuc.gr/dl/dias/2816970E-E37F-40EB-8086-ADB4FE55C026"><efrbr-work:titleOfTheWork>Reduced dimensionality space for post placement quality inspection of components based on neural networks.</efrbr-work:titleOfTheWork></efrbr-work:work><efrbr-expression:expression identifier="http://purl.tuc.gr/dl/dias/2816970E-E37F-40EB-8086-ADB4FE55C026"><efrbr-expression:titleOfTheExpression>Reduced dimensionality space for post placement quality inspection of components based on neural networks.</efrbr-expression:titleOfTheExpression><efrbr-expression:formOfExpression vocabulary="DIAS:TYPES">
            Πλήρης Δημοσίευση σε Συνέδριο
            Conference Full Paper
         </efrbr-expression:formOfExpression><efrbr-expression:dateOfExpression type="issued">2015-10-25</efrbr-expression:dateOfExpression><efrbr-expression:dateOfExpression type="published">2004</efrbr-expression:dateOfExpression><efrbr-expression:languageOfExpression vocabulary="iso639-1">en</efrbr-expression:languageOfExpression><efrbr-expression:summarizationOfContent>The emergence of surface mount technology devices has resulted in several important advantages including increased component density and size reduction on the printed circuit board, on the expense of quality inspection. Classical visual inspection techniques require time-consuming image processing to improve the accuracy of the inspected results. In this paper we reduce the computational complexity of classical machine vision approaches by proposing two neural network based techniques. In the first we maintain image information only in the form of edges, whereas the second we preserve the entire content of info but compressed in a single dimension through image projections. Both algorithms are tested on real industrial data. The quality of inspection is preserved while reducing the computational time.</efrbr-expression:summarizationOfContent><efrbr-expression:useRestrictionsOnTheExpression type="creative-commons">http://creativecommons.org/licenses/by/4.0/</efrbr-expression:useRestrictionsOnTheExpression><efrbr-expression:note type="page range">275-280</efrbr-expression:note><efrbr-expression:note type="conference name">European Symposium on Artificial Neural Networks</efrbr-expression:note></efrbr-expression:expression><efrbr-person:person identifier="http://users.isc.tuc.gr/~mzervakis"><efrbr-person:nameOfPerson vocabulary="TUC:LDAP">
            Zervakis Michalis
            Ζερβακης Μιχαλης
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            Stefanos K. Goumas
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-person:person identifier="22EBEA72-E245-40AB-B3EB-D2C83DA2C0A1"><efrbr-person:nameOfPerson vocabulary="">
            George Rovithakis
         </efrbr-person:nameOfPerson></efrbr-person:person><efrbr-concept:concept identifier="http://id.loc.gov/authorities/subjects/sh85082769"><efrbr-concept:termForTheConcept>
            Applied mechanics
            Engineering, Mechanical
            mechanics applied
            applied mechanics
            engineering mechanical
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