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- W4379117978 abstract "As a direct result of the COVID-19 epidemic, persons who are hard of hearing or deaf have lately been confronted with new obstacles. The health of this population is negatively impacted in a variety of ways, including restricted access to vital health care services and information, social and emotional difficulties, and poor health outcomes, amongst other things. The purpose of this study is to present a revolutionary word-based Moroccan Sign Language Database for Emergency Situations: Use case COVID-19 (MSL-COVID19). Twenty one individuals, ranging in age from 5 to 30 years old (9 females and 12 men), have recorded films of 15 Moroccan words being used in real-world contexts, with each individual contributing 10 examples. A video dataset such as this one is essential in order to support members of the deaf community who rely on sign language as their primary method of communication in crisis situations. Researchers in academia who are working on vision-based sign language identification as well as hand gesture recognition will find the dataset to be very useful. Since the database was based on an experimental investigation, it was also discovered that it may be exploited as a benchmark dataset for the creation of new and improved methods for recognizing the hand movements of words in Moroccan sign language." @default.
- W4379117978 created "2023-06-03" @default.
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- W4379117978 date "2023-01-01" @default.
- W4379117978 modified "2023-09-28" @default.
- W4379117978 title "A Word-Based Moroccan Sign Language Dataset for Emergency Situations: Use Case COVID-19" @default.
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- W4379117978 doi "https://doi.org/10.1007/978-3-031-35248-5_40" @default.
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