Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/27678
DC FieldValueLanguage
dc.contributor.authorKralevska, Aen_US
dc.contributor.authorTrajanov, Ren_US
dc.contributor.authorGievska, Sonjaen_US
dc.date.accessioned2023-09-04T10:14:05Z-
dc.date.available2023-09-04T10:14:05Z-
dc.date.issued2022-05-23-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/27678-
dc.description.abstractThe objective for developing a real-time sign language recognition system is twofold: improving inter-personal communication and supporting inclusive human-computer interaction with hearing-impaired population using a particular sign language. This study describes the design and implementation of a system for real-time Macedonian Sign Language recognition in images and videos. A robust and lightweight model was proposed based on transfer learning of suitable pretrained architectures, namely, Single Shot Detector (SSD) MobileNetV2 and SSD MobileNetV2 FPNLite. The proposed models were fine-tuned and extensively evaluated in a number of diverse scenarios to account for the inherent difficulties in recognizing particular letters. In the absence of publicly available dataset, we have created a dataset consisting of two-handed images of 28 out of 31 letters of the Macedonian alphabet; the three letters expressed by dynamic gestures were excluded from the study. The results point out to a state-of-the-art prediction accuracy on the classification task of Macedonian sign language alphabet.en_US
dc.publisherIEEEen_US
dc.subjectMacedonian sign language recognition , real-time recognition system , transfer learning , Single Shot Detector (SSD), MobileNeten_US
dc.titleReal-time Macedonian Sign Language Recognition System by using Transfer Learningen_US
dc.typeProceeding articleen_US
dc.relation.conference2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO)en_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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