SignMamba: Sparse spatial-temporal state-space modeling for continuous sign language recognition.
- DOI
- 10.1016/j.neunet.2026.109530
- Published
- 2026 Aug 19
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109530,
title = {SignMamba: Sparse spatial-temporal state-space modeling for continuous sign language recognition.},
author = {Yang XH and Wang G and Hu HX and Wei D and Chen ZW and Liu S and Feng Y},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109530},
url = {https://doi.org/10.1016/j.neunet.2026.109530}
}RIS
TY - JOUR TI - SignMamba: Sparse spatial-temporal state-space modeling for continuous sign language recognition. AU - Yang XH AU - Wang G AU - Hu HX AU - Wei D AU - Chen ZW AU - Liu S AU - Feng Y PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109530 UR - https://doi.org/10.1016/j.neunet.2026.109530 ER -
APA
XH, Y., G, W., HX, H., D, W., ZW, C., S, L., & Y, F. (2026). SignMamba: Sparse spatial-temporal state-space modeling for continuous sign language recognition.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109530
Source records
- pubmed · retrieved 2026-09-25T23:08:20.748Z