A machine learning approach for grain crop's seed classification in purifying separation

A. V. Vlasov, A. S. Fadeev

Research output: Contribution to journalConference article

3 Citations (Scopus)


The paper presents a study of the machine learning ability to classify seeds of a grain crop in order to improve purification processing. The main seed features that are hard to separate with mechanical methods are resolved with the use of a machine learning approach. A special training image set was retrieved in order to check if the stated approach is reasonable to use. A set of tests is provided to show the effectiveness of the machine learning for the stated task. The ability to improve the approach with deep learning in further research is described.

Original languageEnglish
Article number012177
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 1 Jul 2017
EventInternational Conference on Information Technologies in Business and Industry 2016 - Tomsk, Russian Federation
Duration: 21 Sep 201623 Sep 2016


ASJC Scopus subject areas

  • Physics and Astronomy(all)

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