"We tested the effectiveness of our mask in real experiments by printing a design on it,
They explained this by saying that the COVID-19 pandemicmade wearing masks a habit, which helped many facial recognition systems to adapt. Now, however, the researchers have used a gradient-based optimization process to create a mask that will help falsely classify each user, whether male or female.
Face recognition models can trainrecognize people wearing unusual masks. Alternatively, each masked face image can be pre-processed at the output stage to make it look like the person is wearing a standard mask.
The researchers relied on the fact thatface recognition compares two parts of a face and tries to answer the question of whether they belong to the same person. Therefore, scientists generated an unusual image that continues the face of the mask owner (sometimes this pattern resembles an animal). This approach confuses the algorithms, and it can only in some cases identify a person. So they generated separate drawings for each user based on their facial features.
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