Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine learning based localization and classification with atomic
  magnetometers   We demonstrate identification of position, material, orientation and shape of
objects imaged by an $^{85}$Rb atomic magnetometer performing electromagnetic
induction imaging supported by machine learning. Machine learning maximizes the
information extracted from the images created by the magnetometer,
demonstrating the use of hidden data. Localization 2.6 times better than the
spatial resolution of the imaging system and successful classification up to
97$\%$ are obtained. This circumvents the need of solving the inverse problem,
and demonstrates the extension of machine learning to diffusive systems such as
low-frequency electrodynamics in media. Automated collection of task-relevant
information from quantum-based electromagnetic imaging will have a relevant
impact from biomedicine to security.

27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
1
The categories of this paper are: cs
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg