Novel spatio-temporal continuous sign language recognition using an attentive multi-feature network

HIGHLIGHTS

• who: Wisnu Aditya et al. from the Department of Computer Science and Information Engineering, National Central University, Taoyuan City, Taiwan have published the research: Novel Spatio-Temporal Continuous Sign Language Recognition Using an Attentive Multi-Feature Network, in the Journal: Sensors 2022, 22, 6452. of 26/08/2022
• what: Given video streams the authors aim to correctly detect unsegmented signs related to continuous sign language recognition (CSLR). The authors propose continuous sign language recognition using the attentive multi-feature network to enhance CSLR by providing extra keypoint features. The aim of this approach is to . . .
  

   

  

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