CBAM-DenseNet with multi-feature quality filtering: advancing accuracy in small-sample iris recognition.

Pang Y, Wang Z, Jiang N, Qin J, Li S

DOI: 10.3389/frai.2025.1714882
Published: 2025
Container: Frontiers in artificial intelligence
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/frai.2025.1714882,
  title = {CBAM-DenseNet with multi-feature quality filtering: advancing accuracy in small-sample iris recognition.},
  author = {Pang Y and Wang Z and Jiang N and Qin J and Li S},
  year = {2025},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2025.1714882},
  url = {https://doi.org/10.3389/frai.2025.1714882}
}

RIS

TY  - JOUR
TI  - CBAM-DenseNet with multi-feature quality filtering: advancing accuracy in small-sample iris recognition.
AU  - Pang Y
AU  - Wang Z
AU  - Jiang N
AU  - Qin J
AU  - Li S
PY  - 2025
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2025.1714882
UR  - https://doi.org/10.3389/frai.2025.1714882
ER  -

APA

Y, P., Z, W., N, J., J, Q., & S, L. (2025). CBAM-DenseNet with multi-feature quality filtering: advancing accuracy in small-sample iris recognition.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2025.1714882

Source records

pubmed · retrieved 2026-09-26T00:40:31.991Z