Walking stability prediction for pedestrians using gait energy images and hybrid deep and few-shot learning models.
- DOI
- 10.1038/s41598-026-61650-z
- Published
- 2026 Jul 17
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-61650-z,
title = {Walking stability prediction for pedestrians using gait energy images and hybrid deep and few-shot learning models.},
author = {Taha M and Fares A and Yamaguchi H and Zaky AB},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-61650-z},
url = {https://doi.org/10.1038/s41598-026-61650-z}
}RIS
TY - JOUR TI - Walking stability prediction for pedestrians using gait energy images and hybrid deep and few-shot learning models. AU - Taha M AU - Fares A AU - Yamaguchi H AU - Zaky AB PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-61650-z UR - https://doi.org/10.1038/s41598-026-61650-z ER -
APA
M, T., A, F., H, Y., & AB, Z. (2026). Walking stability prediction for pedestrians using gait energy images and hybrid deep and few-shot learning models.. Scientific reports. https://doi.org/10.1038/s41598-026-61650-z
Source records
- pubmed · retrieved 2026-11-10T18:53:16.285Z