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Defect detection and classfiication: statistical learning approach - Part II
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
Volvo Group Trucks Operations.
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2019 (English)Report (Other academic)
Place, publisher, year, edition, pages
2019. , p. 56
Keywords [en]
Statistical learning, probabilistic classification, defect detection, automated quality inspection
National Category
Probability Theory and Statistics Signal Processing Manufacturing, Surface and Joining Technology
Research subject
Mathematical Statistics
Identifiers
URN: urn:nbn:se:umu:diva-161255OAI: oai:DiVA.org:umu-161255DiVA, id: diva2:1333262
Funder
Vinnova, 2015-03706Available from: 2019-07-01 Created: 2019-07-01 Last updated: 2019-07-19Bibliographically approved

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Pya Arnqvist, NatalyaNgendangenzwa, BlaiseNilsson, LeifYu, Jun

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CiteExportLink to record
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