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<record>
  <title>Detection of Irregularities on Automotive Semiproducts</title>
  <journal>Transactions on Machine Design</journal>
  <author>Erik Dovgan, Klemen Gantar, Valentin Koblar, Bogdan Filipic</author>
  <volume>7</volume>
  <issue>2</issue>
  <year>2019</year>
  <doi></doi>
  <url>http://www.dline.info/tmd/fulltext/v7n2/tmdv7n2_4.pdf</url>
  <abstract>he use of applications for automated inspection of semiproducts is increasing in various industries, including the automotive industry. This paper presents the development of an application for automated visual detection of irregularities on commutators that are parts of vehicleâ€™s fuel pumps. Each type of irregularity is detected on a partition of the commutator image. The initial results show that such an automated inspection is able to reliably detect irregularities on commutators. In addition, the results confirm that the set of attributes used to build the classifiers for detecting individual types of irregularities and the priority of these classifiers significantly influence the classification accuracy.
 </abstract>
</record>
