Ear biometrics in forensic identification: from ear similarity quantification to kinship verification driven by deep learning approaches
- DOI
- 10.1007/s00414-025-03636-6
- Published
- 2025-10-15
- Container
- International Journal of Legal Medicine
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s00414-025-03636-6,
title = {Ear biometrics in forensic identification: from ear similarity quantification to kinship verification driven by deep learning approaches},
author = {Xindi Wang and Zibo Zhao and Yufei Yang and Bo Liu and Chengye Zhou and Chuanxu Wang and Haibo Luo and Feng Song},
year = {2025},
journal = {International Journal of Legal Medicine},
doi = {10.1007/s00414-025-03636-6},
url = {https://doi.org/10.1007/s00414-025-03636-6}
}RIS
TY - JOUR TI - Ear biometrics in forensic identification: from ear similarity quantification to kinship verification driven by deep learning approaches AU - Xindi Wang AU - Zibo Zhao AU - Yufei Yang AU - Bo Liu AU - Chengye Zhou AU - Chuanxu Wang AU - Haibo Luo AU - Feng Song PY - 2025 JO - International Journal of Legal Medicine DO - 10.1007/s00414-025-03636-6 UR - https://doi.org/10.1007/s00414-025-03636-6 ER -
APA
Wang, X., Zhao, Z., Yang, Y., Liu, B., Zhou, C., Wang, C., Luo, H., & Song, F. (2025). Ear biometrics in forensic identification: from ear similarity quantification to kinship verification driven by deep learning approaches. International Journal of Legal Medicine. https://doi.org/10.1007/s00414-025-03636-6
Source records
- crossref · retrieved 2026-11-07T11:33:20.710Z