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Caramazza, Piergiorgio; Boccolini, Alessandro; Buschek, Daniel; Hullin, Matthias; Higham, Catherine F.; Henderson, Robert; Murray-Smith, Roderick and Faccio, Daniele (2018): Neural network identification of people hidden from view with a single-pixel, single-photon detector. In: Scientific Reports, Vol. 8, 11945 [PDF, 1MB]


Light scattered from multiple surfaces can be used to retrieve information of hidden environments. However, full three-dimensional retrieval of an object hidden from view by a wall has only been achieved with scanning systems and requires intensive computational processing of the retrieved data. Here we use a non-scanning, single-photon single-pixel detector in combination with a deep convolutional artificial neural network: this allows us to locate the position and to also simultaneously provide the actual identity of a hidden person, chosen from a database of people (N = 3). Artificial neural networks applied to specific computational imaging problems can therefore enable novel imaging capabilities with hugely simplified hardware and processing times.

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