文章基本信息

标题：Neural network identification of people hidden from view with a single-pixel, single-photon detector
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作者：Piergiorgio Caramazza ; Alessandro Boccolini ; Daniel Buschek 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2018
卷号：8
期号：1
页码：11945
DOI：10.1038/s41598-018-30390-0
语种：English
出版社：Springer Nature
摘要：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.