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  • Open Access

    REVIEW

    A Survey on Chinese Sign Language Recognition: From Traditional Methods to Artificial Intelligence

    Xianwei Jiang1, Yanqiong Zhang1,*, Juan Lei1, Yudong Zhang2,3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1-40, 2024, DOI:10.32604/cmes.2024.047649 - 16 April 2024

    Abstract Research on Chinese Sign Language (CSL) provides convenience and support for individuals with hearing impairments to communicate and integrate into society. This article reviews the relevant literature on Chinese Sign Language Recognition (CSLR) in the past 20 years. Hidden Markov Models (HMM), Support Vector Machines (SVM), and Dynamic Time Warping (DTW) were found to be the most commonly employed technologies among traditional identification methods. Benefiting from the rapid development of computer vision and artificial intelligence technology, Convolutional Neural Networks (CNN), 3D-CNN, YOLO, Capsule Network (CapsNet) and various deep neural networks have sprung up. Deep Neural… More >

  • Open Access

    ARTICLE

    An Optimized Convolutional Neural Network with Combination Blocks for Chinese Sign Language Identification

    Yalan Gao, Yanqiong Zhang, Xianwei Jiang*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 95-117, 2022, DOI:10.32604/cmes.2022.019970 - 02 June 2022

    Abstract (Aim) Chinese sign language is an essential tool for hearing-impaired to live, learn and communicate in deaf communities. Moreover, Chinese sign language plays a significant role in speech therapy and rehabilitation. Chinese sign language identification can provide convenience for those hearing impaired people and eliminate the communication barrier between the deaf community and the rest of society. Similar to the research of many biomedical image processing (such as automatic chest radiograph processing, diagnosis of chest radiological images, etc.), with the rapid development of artificial intelligence, especially deep learning technologies and algorithms, sign language image recognition ushered… More >

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