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Titlebook: Handbook of Biometric Anti-Spoofing; Presentation Attack Sébastien Marcel,Mark S. Nixon,Nicholas Evans Book 20192nd edition Springer Natur

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樓主: 重婚
31#
發(fā)表于 2025-3-27 00:19:03 | 只看該作者
https://doi.org/10.1007/978-3-663-05215-9urrent neural networks and compares their PAD performance to solutions based on the parametric Clynes–Kohn model and various classification techniques. Experiments with 166 distinct eyes of 84 subjects show that the best data-driven solution, one based on long short-term memory, was able to correctl
32#
發(fā)表于 2025-3-27 05:00:37 | 只看該作者
33#
發(fā)表于 2025-3-27 09:19:53 | 只看該作者
https://doi.org/10.1007/978-90-368-1234-4he significant advances in face-PAD research since the publication of the first edition of this book. In addition to new face-PAD methods designed for color images, we also discuss advances involving other imaging modalities, such as near-infrared (NIR) and thermal imaging. Research on detecting var
34#
發(fā)表于 2025-3-27 12:41:49 | 只看該作者
https://doi.org/10.1007/978-981-99-6331-7 containing a wide range of face presentation attacks. Obtained results suggest that the proposed features are effective for this task, and we empirically show that our approach performs better than state-of-the-art rPPG-based presentation attack detection algorithms.
35#
發(fā)表于 2025-3-27 13:56:45 | 只看該作者
Sébastien Marcel,Mark S. Nixon,Nicholas EvansThe definitive study of biometric anti-spoofing (a.k.a., biometric presentation attack detection).Discusses spoofing methods, vulnerabilities of biometric systems and countermeasures to spoofing attac
36#
發(fā)表于 2025-3-27 19:54:58 | 只看該作者
37#
發(fā)表于 2025-3-28 01:07:23 | 只看該作者
38#
發(fā)表于 2025-3-28 04:06:14 | 只看該作者
39#
發(fā)表于 2025-3-28 07:33:26 | 只看該作者
Handbook of Biometric Anti-Spoofing978-3-319-92627-8Series ISSN 2191-6586 Series E-ISSN 2191-6594
40#
發(fā)表于 2025-3-28 10:53:43 | 只看該作者
An Introduction to Fingerprint Presentation Attack Detection developments for that purpose in the last two decades. After a review of selected literature in the field, we also revisit the potential of quality assessment for presentation attack detection. We believe that, beyond the interest that the described techniques may intrinsically have by themselves,
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