Research Article
An Optimized Seven-Layer Convolutional Neural Network with Data Augmentation for Classification of Chinese Fingerspelling Sign Language
@INPROCEEDINGS{10.1007/978-3-030-82565-2_3, author={Yalan Gao and Rongxin Zhu and Ruina Gao and Yuxiang Weng and Xianwei Jiang}, title={An Optimized Seven-Layer Convolutional Neural Network with Data Augmentation for Classification of Chinese Fingerspelling Sign Language}, proceedings={Multimedia Technology and Enhanced Learning. Third EAI International Conference, ICMTEL 2021, Virtual Event, April 8--9, 2021, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2021}, month={7}, keywords={Convolutional neural network Data augmentation Chinese fingerspelling sing language Batch normalization ReLU Maximum pooling Dropout}, doi={10.1007/978-3-030-82565-2_3} }- Yalan Gao
Rongxin Zhu
Ruina Gao
Yuxiang Weng
Xianwei Jiang
Year: 2021
An Optimized Seven-Layer Convolutional Neural Network with Data Augmentation for Classification of Chinese Fingerspelling Sign Language
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-030-82565-2_3
Abstract
Sign language recognition especially finger language recognition facilitates the life of deaf people in China. It overcomes many difficulties and provides convenience for deaf people’s life. In this paper, we used the advanced convolutional neural network to extract the different characteristics of the input. We created an optimized seven-layer CNN, including five convolution layers for feature extraction and two fully connected layers for classification to enhance the original signal function and reduce noise after operation. Some advanced techniques such as batch normalization, ReLu and dropout were employed to optimize the neural network. Meanwhile, we adopted data augmentation technology, which not only expanded the data set and improve the performance of machine learning algorithm, but also avoided the over-fitting problem. The experimental results show that the average recognition accuracy reaches 91.99 ± 1.21%, which indicate an excellent property.
