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Face Recognition Software Shows Improvement in Recognizing Masked Faces A new study of face recognition technology created after the onset of the COVID-19 pandemic shows that some software developers have made demonstrable progress at recognizing masked faces. The findings, produced by the National Institute of Standards and Technology (NIST), are detailed in a new report called Ongoing Face Recognition Vendor Test (FRVT) Part 6B: Face Recognition Accuracy with Face Masks Using Post-COVID-19 Algorithms (NISTIR 8331). It is the agency’s first study that measures the performance of face recognition algorithms developed following the arrival of the pandemic. A previous report from July explored the effect of masked faces on algorithms submitted before March 2020, indicating that software available before the pandemic often had more trouble with masked faces. Read More In Case You Missed It NIST Launches Studies Into Masks’ Effect on Face Recognition Software July 27, 2020 Researchers found that algorithms created before the pandemic generally perform less accurately with digitally masked faces. Read More