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Transferable non-invasive modal fusion-transformer (NIMFT) for end-to-end hand gesture recognition.

Tianxiang XuKunkun ZhaoYuxiang HuLiang LiWei WangFulin WangYu-Xuan ZhouJianqing Li
Published in: Journal of neural engineering (2024)
The NIMFT is a novel end-to-end HGR model, utilizes a non-invasive MCA mechanism to integrate long-range intermodal information effectively. Compared to recent modal fusion models, it demonstrates superior performance in inter-subject experiments and offers higher training efficiency and accuracy levels through transfer learning than subject-specific approaches.
Keyphrases
  • healthcare
  • social media