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Boundary-Adaptive Encoder With Attention Method for Chinese Sign Language Recognition
2021
IEEE Access
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 on recurrent networks cannot discover and leverage the hierarchical structure of sign language well. In this paper, we propose a novel encoder-decoder method based on boundary adaptive learning for Chinese SLR. The hierarchical structure of
doi:10.1109/access.2021.3078638
fatcat:v24getlbj5axlkldzhafibzstu