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Reduced dimensionality space for post placement quality inspection of components based on neural networks.

Zervakis Michalis, Stefanos K. Goumas, George Rovithakis

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URIhttp://purl.tuc.gr/dl/dias/2816970E-E37F-40EB-8086-ADB4FE55C026-
Identifierhttps://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2004-96.pdf-
Languageen-
Extent6 pagesen
TitleReduced dimensionality space for post placement quality inspection of components based on neural networks.en
CreatorZervakis Michalisen
CreatorΖερβακης Μιχαληςel
CreatorStefanos K. Goumasen
CreatorGeorge Rovithakisen
Content SummaryThe 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.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-25-
Date of Publication2004-
SubjectApplied mechanicsen
SubjectEngineering, Mechanicalen
Subjectmechanics applieden
Subjectapplied mechanicsen
Subjectengineering mechanicalen
Bibliographic CitationS. Goumas, M.E. Zervakis, G.A. Rovithakis .(2004).Reduced dimensionality space for post placement quality inspection of components based on neural networks.Presented at European Symposium on Artificial Neural Networks.[online].Available:https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2004-96.pdfen

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