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.
95.5% accuracy is abysmal for any use case these people want to use it for
It’s not at all bad for an initial proof of concept.
what if you combine it with other types of imaging
Dingdingding