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Conditional Face Image Manipulation Detection: Combining Algorithm and Human Examiner Decisions.

, , , , , , , , and . IH&MMSec, page 41-46. ACM, (2024)

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Face morph detection for unknown morphing algorithms and image sources: a multi-scale block local binary pattern fusion approach., , , and . IET Biom., 9 (6): 278-289 (2020)Iris-biometric comparators: Minimizing trade-offs costs between computational performance and recognition accuracy., , and . ICDP, page 1-6. IET / IEEE, (2011)Synthetic Data in Human Analysis: A Survey., , , , , and . CoRR, (2022)Demographic Bias in Biometrics: A Survey on an Emerging Challenge., , , , and . CoRR, (2020)Deep Learning-based Single Image Face Depth Data Enhancement., , and . CoRR, (2020)A Study of Hand-Crafted and Naturally Learned Features for Fingerprint Presentation Attack Detection., , , , , and . Handbook of Biometric Anti-Spoofing, 2nd Ed., Springer, (2019)Synthetic Data for the Mitigation of Demographic Biases in Face Recognition., , , , , , , and . IJCB, page 1-9. IEEE, (2023)Incremental iris recognition: A single-algorithm serial fusion strategy to optimize time complexity., , and . BTAS, page 1-6. IEEE, (2010)Exploring Quality Scores for Workload Reduction in Biometric Identification., , , , and . IWBF, page 1-6. IEEE, (2022)Deep Learning-Based Semantic Segmentation for Touchless Fingerprint Recognition., , , and . ICPR Workshops (8), volume 12668 of Lecture Notes in Computer Science, page 154-168. Springer, (2020)