A machine learning approach for grain crop's seed classification in purifying separation; Journal of Physics: Conference Series; Vol. 803 : Information Technologies in Business and Industry (ITBI2016)
| Parent link: | Journal of Physics: Conference Series Vol. 803 : Information Technologies in Business and Industry (ITBI2016).— 2017.— [012177, 6 p.] |
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| Awdur Corfforaethol: | |
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| Crynodeb: | 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. |
| Iaith: | Saesneg |
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2017
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| Mynediad Ar-lein: | http://dx.doi.org/10.1088/1742-6596/803/1/012177 http://earchive.tpu.ru/handle/11683/38212 |
| Fformat: | Electronig Pennod Llyfr |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654468 |
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| 200 | 1 | |a A machine learning approach for grain crop's seed classification in purifying separation |f A. V. Vlasov, A. S. Fadeev | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 14 tit.] | ||
| 330 | |a 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. | ||
| 461 | 0 | |0 (RuTPU)RU\TPU\network\3526 |t Journal of Physics: Conference Series | |
| 463 | 0 | |0 (RuTPU)RU\TPU\network\19875 |t Vol. 803 : Information Technologies in Business and Industry (ITBI2016) |o International Conference, 21–26 September 2016, Tomsk, Russian Federation |o [proceedings] |f National Research Tomsk Polytechnic University (TPU) ; eds. N. V. Martyushev ; V. S. Avramchuk ; V. A. Faerman |v [012177, 6 p.] |d 2017 | |
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| 701 | 1 | |a Fadeev |b A. S. |c specialist in the field of informatics and computer technology |c Vice-Rector for Digitalization - Director of the Digital Educational Technologies Center, Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences |f 1981- |g Aleksandr Sergeevich |3 (RuTPU)RU\TPU\pers\35328 |9 18588 | |
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