Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exploit imaging through opaque wall via deep learning   Imaging through scattering media is encountered in many disciplines or
sciences, ranging from biology, mesescopic physics and astronomy. But it is
still a big challenge because light suffers from multiple scattering is such
media and can be totally decorrelated. Here, we propose a deep-learning-based
method that can retrieve the image of a target behind a thick scattering
medium. The method uses a trained deep neural network to fit the way of mapping
of objects at one side of a thick scattering medium to the corresponding
speckle patterns observed at the other side. For demonstration, we retrieve the
images of a set of objects hidden behind a 3mm thick white polystyrene slab,
the optical depth of which is 13.4 times of the scattering mean free path. Our
work opens up a new way to tackle the longstanding challenge by using the
technique of deep learning.

10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
13
The categories of this paper are: quant-ph
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin