Abstract
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
Highlights
Sign language is a form of communication and exchange of ideas by people who are hearing-impaired or unable to speak
The standard convolutional neural network covers all important phases of traditional computer vision methods: feature extraction and reduction, and classification
The convolutional layer is the core of the convolutional neural network, and most calculations are performed in the convolutional layer
Summary
Sign language is a form of communication and exchange of ideas by people who are hearing-impaired or unable to speak. OBJECTIVES: We propose a nine-layer convolutional neural network (CNN) for 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. In the world, there are thousands of people suffering from hearing impairment [1]. This special group of people is called deaf-mutes, and they cannot communicate through language as normal people can. Fingerspelling language focuses on 30 basic finger languages (including 26 basic pinyin letters and 4 upturned tongues), which can be combined to express pinyin or some special meaning
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