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A Covariate-Adjusted Homogeneity Test with Application to Facial Recognition Accuracy Assessment
Ordinal scores occur commonly in medical imaging studies and in black-box forensic studies \citep{Phillips:2018}.
Human-Machine Comparison for Cross-Race Face Verification: Race Bias at the Upper Limits of Performance?
Two top-performing face recognition systems from the Face Recognition Vendor Test-ongoing performed the same test (7).
Distill and De-bias: Mitigating Bias in Face Verification using Knowledge Distillation
In D&D, we train a teacher network on images from one category of an attribute; e. g. light skintone.
Face Identification Proficiency Test Designed Using Item Response Theory
Multiple tests of equal difficulty can be constructed then using subsets of items.
Four Principles of Explainable AI as Applied to Biometrics and Facial Forensic Algorithms
Traditionally, researchers in automatic face recognition and biometric technologies have focused on developing accurate algorithms.
Accuracy comparison across face recognition algorithms: Where are we on measuring race bias?
We discuss data driven factors (e. g., image quality, image population statistics, and algorithm architecture), and scenario modeling factors that consider the role of the "user" of the algorithm (e. g., threshold decisions and demographic constraints).
How are attributes expressed in face DCNNs?
In the final fully connected layer of the networks, we found the order of expressivity for facial attributes to be Age > Sex > Yaw.
