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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/54304
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dc.contributor.authorNour Atamni-
dc.contributor.authorSaid Naamneh-
dc.contributor.authorJihad El-Sana-
dc.coverage.spatialМинскen_US
dc.date.accessioned2024-02-21T11:32:57Z-
dc.date.available2024-02-21T11:32:57Z-
dc.date.issued2023-
dc.identifier.citationNour Atamni. Hand Action Recognition / Nour Atamni, Said Naamneh, Jihad El-Sana // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 153–157.en_US
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/54304-
dc.description.abstractThis paper presents a new dataset for hand action detection for manipulating (assembling and dismantling) mechanical devices and an action detection model based on Transformers. An entry in this dataset is a first-person-view video segment that shows hands performing an action. These hands may utilize a tool and act on an object of the device. These actions were categorized into 12 classes for simple representation. The deep learning model extracts features from each frame in a video, adds position embedding, and feeds the obtained feature vectors to a Transformer Encoder. The output vector goes through a fully connected network to obtain the final class. We have implemented our model and trained it using the presented dataset. We experimentally evaluate the learning and obtain encouraging results.en_US
dc.language.isoenen_US
dc.publisherBSUen_US
dc.subjectматериалы конференцийen_US
dc.subjecthand recognitionen_US
dc.subjectaction recognitionen_US
dc.subjectaction recognition dataseten_US
dc.titleHand Action Recognitionen_US
dc.typeArticleen_US
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)

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