Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep learning polarization distributions in ferroelectrics from STEM
  data: with and without atom finding   Over the last decade, scanning transmission electron microscopy (STEM) has
emerged as a powerful tool for probing atomic structures of complex materials
with picometer precision, opening the pathway toward exploring ferroelectric,
ferroelastic, and chemical phenomena on the atomic-scale. Analyses to date
extracting a polarization signal from lattice coupled distortions in STEM
imaging rely on discovery of atomic positions from intensity maxima/minima and
subsequent calculation of polarization and other order parameter fields from
the atomic displacements. Here, we explore the feasibility of polarization
mapping directly from the analysis of STEM images using deep convolutional
neural networks (DCNNs). In this approach, the DCNN is trained on the labeled
part of the image (i.e., for human labelling), and the trained network is
subsequently applied to other images. We explore the effects of the choice of
the descriptors (centered on atomic columns and grid-based), the effects of
observational bias, and whether the network trained on one composition can be
applied to a different one. This analysis demonstrates the tremendous potential
of the DCNN for the analysis of high-resolution STEM imaging and spectral data
and highlights the associated limitations.

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The categories of this paper are: hep-ph
2
The categories of this paper are: math
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn