Detection of Micro-Texture Anomalies in Synthetic Fingerprint Forgery Using Generative Adversarial Networks and Diffusion Models in Biometric Authentication Systems
- DOI
- 10.59324/ejtas.2026.4(4).04
- Published
- 2026-07-24
- Container
- European Journal of Theoretical and Applied Sciences
- Publisher
- AMO Publisher
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.59324/ejtas.2026.4-4-.04,
title = {Detection of Micro-Texture Anomalies in Synthetic Fingerprint Forgery Using Generative Adversarial Networks and Diffusion Models in Biometric Authentication Systems},
author = {Mustafa Demirci and Öznur Sari},
year = {2026},
journal = {European Journal of Theoretical and Applied Sciences},
doi = {10.59324/ejtas.2026.4(4).04},
url = {https://doi.org/10.59324/ejtas.2026.4(4).04}
}RIS
TY - JOUR TI - Detection of Micro-Texture Anomalies in Synthetic Fingerprint Forgery Using Generative Adversarial Networks and Diffusion Models in Biometric Authentication Systems AU - Mustafa Demirci AU - Öznur Sari PY - 2026 JO - European Journal of Theoretical and Applied Sciences DO - 10.59324/ejtas.2026.4(4).04 UR - https://doi.org/10.59324/ejtas.2026.4(4).04 ER -
APA
Demirci, M., & Sari, Ö. (2026). Detection of Micro-Texture Anomalies in Synthetic Fingerprint Forgery Using Generative Adversarial Networks and Diffusion Models in Biometric Authentication Systems. European Journal of Theoretical and Applied Sciences. https://doi.org/10.59324/ejtas.2026.4(4).04
Source records
- crossref · retrieved 2026-11-10T11:48:14.940Z