The Sapienza computer scientists say Wi-Fi signals offer superior surveillance potential compared to cameras because they're not affected by light conditions, can penetrate walls and other obstacles, and they're more privacy-preserving than visual images.

[…] The Rome-based researchers who proposed WhoFi claim their technique makes accurate matches on the public NTU-Fi dataset up to 95.5 percent of the time when the deep neural network uses the transformer encoding architecture.

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[–] 1 point 1 year ago

Never said that it wasn’t easy, it’s just harder than with facial recognition. In theory you could do it correctly in a way that it isn’t indentifiable.

Also this works in places where faces are protected

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