Using a deep neural network to improve virtual images of people created using WiFi signals

A trio of researchers at Carnegie Mellon University has taken the use of WiFi signals to identify people in a building to a new level, through the use of a deep neural network. Jiaqi Geng, Dong Huang and Fernando De la Torre suggest, in a paper they have posted to the arXiv preprint server, that their approach allows for creating images on par with RGB cameras.

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