Chinese fingerspelling sign language recognition using a nine-layer convolutional neural network
العنوان: | Chinese fingerspelling sign language recognition using a nine-layer convolutional neural network |
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المؤلفون: | Chengchong Jia, Xianwei Jiang, Ya Gao, Hongli Chen |
المصدر: | EAI Endorsed Transactions on e-Learning, Vol 7, Iss 20 (2021) |
بيانات النشر: | European Alliance for Innovation n.o., 2021. |
سنة النشر: | 2021 |
مصطلحات موضوعية: | Computer science, Speech recognition, convolutional neural network, deaf-mute, 02 engineering and technology, Sign language, Chinese Sign Language, lcsh:Technology, 01 natural sciences, Convolutional neural network, Terminology, Component (UML), batch normalization technology, 0202 electrical engineering, electronic engineering, information engineering, chinese fingerspelling recognition, 0101 mathematics, Contextual image classification, lcsh:T, 010102 general mathematics, sign language recognition, stochastic pooling, language.human_language, language, 020201 artificial intelligence & image processing, lcsh:L, dropout method, lcsh:Education, Fingerspelling, Gesture |
الوصف: | INTRODUCTION: Sign language is a form of communication and exchange of ideas by people who are hearing-impaired or unable to speak. Chinese fingerspelling is an important component of Chinese sign language, which is suitable for denoting terminology and using as the basis of gesture sign language learning. OBJECTIVES: We propose a nine-layer convolutional neural network (CNN) for the classification of Chinese sign language. METHODS: With self-learning and self-organization abilities, CNN is committed to processing data with similar network structure. CNN has a good application prospect in the aspect of image classification andplays a very important role in the classification of Chinese sign language. RESULTS: Through experiments on 1320 data samples of 30 categories, the results show that the classification accuracy based on the nine-layer convolutional neural network can reach up to 89.69± 2.10 %, it can be seen that this method can effectively classify Chinese gestures. CONCLUSION: We proposed a nine-layer convolutional neural network (CNN) that can classify Chinese sign language. |
تدمد: | 2032-9253 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b2c4fd75614330172ce624666668a57 https://doi.org/10.4108/eai.12-10-2020.166555 |
حقوق: | OPEN |
رقم الأكسشن: | edsair.doi.dedup.....8b2c4fd75614330172ce624666668a57 |
قاعدة البيانات: | OpenAIRE |
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