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http://hdl.handle.net/20.500.12188/27678
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kralevska, A | en_US |
dc.contributor.author | Trajanov, R | en_US |
dc.contributor.author | Gievska, Sonja | en_US |
dc.date.accessioned | 2023-09-04T10:14:05Z | - |
dc.date.available | 2023-09-04T10:14:05Z | - |
dc.date.issued | 2022-05-23 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/27678 | - |
dc.description.abstract | The 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.publisher | IEEE | en_US |
dc.subject | Macedonian sign language recognition , real-time recognition system , transfer learning , Single Shot Detector (SSD), MobileNet | en_US |
dc.title | Real-time Macedonian Sign Language Recognition System by using Transfer Learning | en_US |
dc.type | Proceeding article | en_US |
dc.relation.conference | 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO) | en_US |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Conference papers |
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