Comparison of object classification methods in seed stream separation; Advances in Computer Science Research; Vol. 72 : Information technologies in Science, Management, Social sphere and Medicine (ITSMSSM 2017)
| Parent link: | Advances in Computer Science Research Vol. 72 : Information technologies in Science, Management, Social sphere and Medicine (ITSMSSM 2017).— 2017.— [P. 179-181] |
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| Riassunto: | Title screen The paper presents a study of machine learning approaches to detect and classify seeds of a grain crop in order to enhance agricultural seed purification line. The main features of seeds that are hard to recognize during a separation with mechanical methods are resolved with the help of machine learning approach. The main machine learning methods used in research was traditional machine learning and deep learning based on neural networks. A special training image database was retrieved in order to check if the stated approaches are reasonable to use and develop. A set of tests is provided to show the effectiveness of the machine learning applied to solve the stated problem. |
| Lingua: | inglese |
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2017
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| Accesso online: | http://dx.doi.org/10.2991/itsmssm-17.2017.38 |
| Natura: | Elettronico Capitolo di libro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=657526 |