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

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

Bibliographic Details
Parent link:Journal of Physics: Conference Series
Vol. 803 : Information Technologies in Business and Industry (ITBI2016).— 2017.— [012177, 6 p.]
Main Author: Vlasov A. V. Andrey Vladimirovich
Corporate Author: Национальный исследовательский Томский политехнический университет (ТПУ) Институт кибернетики (ИК) Кафедра автоматики и компьютерных систем (АИКС)
Other Authors: Fadeev A. S. Aleksandr Sergeevich
Summary:Title screen
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.
Published: 2017
Subjects:
электронный ресурс
труды учёных ТПУ
машинное обучение
классификация
семена
зерновые культуры
очистка
Online Access:http://dx.doi.org/10.1088/1742-6596/803/1/012177
http://earchive.tpu.ru/handle/11683/38212
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654468

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