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Online recognition of mobile objects

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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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