dc.contributor.author | CIORBA, Dina | |
dc.contributor.author | LEȘCO, Andrei | |
dc.contributor.author | DODI, Cristian-Dumitru | |
dc.contributor.author | PLEȘCA, Anișoara-Ionela | |
dc.date.accessioned | 2021-06-24T08:05:13Z | |
dc.date.available | 2021-06-24T08:05:13Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | CIORBA, Dina, LEȘCO, Andrei, DODI, Cristian-Dumitru, PLEȘCA, Anișoara-Ionela. Online recognition of mobile objects. In: Conferinţa Tehnico-Ştiinţifică a Studenţilor, Masteranzilor şi Doctoranzilor, Universitatea Tehnică a Moldovei, 23-25 martie, 2021. Chişinău, 2021, vol. 1, pp. 275-278. ISBN 978-9975-45-699-9. | en_US |
dc.identifier.isbn | 978-9975-45-699-9 | |
dc.identifier.uri | http://repository.utm.md/handle/5014/16229 | |
dc.description.abstract | The system designed for the recognition of geometrical figures that are moving on a conveyor belt was developed by using the Canny edge detection algorithm, where the objects are identified with the maximum accuracy. The Canny algorithm provided a 88% accuracy result, alongside the Bilateral Filtering and Thresholding algorithms, which were also used for image processing experiments. To enable the training of machine learning models to classify the objects according to the defined labels, the AutoML Vision was used as a part of the system brain - Artificial Intelligence. The current project describes the flow of implementing the system with real images of the results and deductions. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universitatea Tehnică a Moldovei | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | object detection | en_US |
dc.subject | internet of things | en_US |
dc.subject | machine learning | en_US |
dc.subject | classification | en_US |
dc.subject | computer vision | en_US |
dc.title | Online recognition of mobile objects | en_US |
dc.type | Article | en_US |
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