Results 11 to 20 of about 551 (165)
KuSL2023: A standard for Kurdish sign language detection and classification using hand tracking and machine learning [PDF]
MethodsXSign Language Recognition (SLR) plays a vital role in enhancing communication for the deaf and hearing-impaired communities, yet there has been a lack of resources for Kurdish Sign Language (KuSL).
Karwan M. Hama Rawf
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Journal of Disability Research, 2023 Sign language recognition is an effective solution for individuals with disabilities to communicate with others. It helps to convey information using sign language.
Radwa Marzouk +3 more
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A Novel Communication System For Deaf And Dumb People using gesture [PDF]
ITM Web of Conferences, 2020 Human Beings know each other and contact with themselves through thoughts and ideas.The best way to present our idea is through speech. Some people don’t have the power of speech; the only way they communicate with others is through sign language.
Ambavane Pritesh +5 more
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Machine learning methods for sign language recognition: A critical review and analysis
Intelligent Systems with Applications, 2021 Sign language is an essential tool to bridge the communication gap between normal and hearing-impaired people. However, the diversity of over 7000 present-day sign languages with variability in motion position, hand shape, and position of body parts ...
I.A. Adeyanju, O.O. Bello, M.A. Adegboye
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Boundary-Adaptive Encoder With Attention Method for Chinese Sign Language Recognition
IEEE Access, 2021 The sign language signal has hierarchically related information over short and long distances. Due to the intricate temporal correlation of input sequences, Chinese sign language recognition (SLR) has a modeling challenge. The conventional encoders based
Shiliang Huang, Zhongfu Ye
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Sensors, 2021 Sign language is the most important way of communication for hearing-impaired people. Research on sign language recognition can help normal people understand sign language. We reviewed the classic methods of sign language recognition, and the recognition
Lu Meng, Ronghui Li
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Multi-Information Spatial–Temporal LSTM Fusion Continuous Sign Language Neural Machine Translation
IEEE Access, 2020 There are two basic problems in sign language recognition (SLR): (a) isolated word SLR and (b) continuous SLR. Most of the existing continuous SLR methods are extensions of the isolated word SLR methods. These methods use the isolated word SLR results as
Qinkun Xiao +3 more
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Computer Methods and Programs in Biomedicine Update, 2022 Background: Sign language is an essential means of communication for hearing-impaired individuals. Objective: We aimed to develop an American sign language recognition dataset and use it in the deep learning model which depends on neural networks to ...
Ahmed KASAPBAŞI +3 more
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Exploring MediaPipe optimization strategies for real-time sign language recognition
CTU Journal of Innovation and Sustainable Development, 2023 The present study meticulously investigates optimization strategies for real-time sign language recognition (SLR) employing the MediaPipe framework. We introduce an innovative multi-modal methodology, amalgamating four distinct Long Short-Term Memory ...
Phuoc Thanh Nguyen +5 more
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Chinese sign language recognition based on surface electromyography and motion information.
PLoS ONE, 2023 Sign language (SL) has strong structural features. Various gestures and the complex trajectories of hand movements bring challenges to sign language recognition (SLR).
Wenyu Li +3 more
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