Please use this identifier to cite or link to this item: http://lib.kart.edu.ua/handle/123456789/18531
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dc.contributor.authorSadovnykov, B.-
dc.contributor.authorZhuchenko, O.-
dc.contributor.authorPerets, K.-
dc.date.accessioned2023-12-11T18:30:09Z-
dc.date.available2023-12-11T18:30:09Z-
dc.date.issued2023-
dc.identifier.citationSadovnykov B. Overview of state-of-the-art image object detection and classification approaches / В. Sadovnykov, О. Zhuchenko, К. Perets // Інформаційно-керуючі системи на залізничному транспорті : тези стендових доповідей та виступів учасників 36-ї Міжнародної науково-практичної конференції "Інформаційно-керуючі системи на залізничному транспорті" (Харків, 16-17 листопада, 2023 р.). – 2023. – № 3 (додаток). – С. 9-10.uk_UA
dc.identifier.issn1681-4886 (print); 2413-3833(online)-
dc.identifier.urihttp://lib.kart.edu.ua/handle/123456789/18531-
dc.description.abstractProblem of object detection and classification has always been a pretty complex and current topic in the computer vision area. A proper solution of this problem will give us a lot of different quality of life improvements. First of all it’s a huge enhancement in the automotive area, manufacturing automation, city traffic control, different kinds of tasks related to children activity monitoring, and this list can be extended even further. Under the “proper” word we mean that object detection and classification algorithms should have good accuracy, ability to process data in real time and save accuracy with some noises, work with low quality input images, and different lighting.uk_UA
dc.language.isoenuk_UA
dc.publisherУкраїнський державний університет залізничного транспортуuk_UA
dc.titleOverview of state-of-the-art image object detection and classification approachesuk_UA
dc.typeThesisuk_UA
Appears in Collections:Том 28 № 3 (додаток)

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