Face perception, Biometrics, Surveillance, Facial recognition system, United States, Null hypothesis
The Critics Were Wrong: NIST Data Shows the Best Facial Recognition Algorithms Are Neither Racist Nor Sexist
@jluan the critics were wrong! i mean, they were right a little bit. but important to keep in mind that they were also wrong
(from here: https://t.co/4tvqyzRJHf)
OpenPatrick Grother, Mei Ngan, and Kayee Hanaoka, Face Recognition Vendor Test (FRVT) Part 3: Demographic Effects (Washington, DC: National Institute of Standards and Technology, December 2019), 3, https://nvlpubs.nist.gov/nistpubs/ir/2019/NIST.IR.8280.pdf#page=6. Algorithms that had lower ...
@jluan the critics were wrong! i mean, they were right a little bit. but important to keep in mind that they were also wrong
(from here: https://t.co/4tvqyzRJHf)
OpenThe Critics Were Wrong: NIST Data Shows the Best Facial Recognition Algorithms Are Neither Racist Nor Sexist
Patrick Grother, Mei Ngan, and Kayee Hanaoka, Face Recognition Vendor Test (FRVT) Part 3: Demographic Effects (Washington, DC: National Institute of Standards and Technology, December ...
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The Critics Were Wrong: NIST Data Shows the Best Facial Recognition Algorithms Are Neither Racist Nor Sexist
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