Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Galaxy Image Translation with Semi-supervised Noise-reconstructed
  Generative Adversarial Networks   Image-to-image translation with Deep Learning neural networks, particularly
with Generative Adversarial Networks (GANs), is one of the most powerful
methods for simulating astronomical images. However, current work is limited to
utilizing paired images with supervised translation, and there has been rare
discussion on reconstructing noise background that encodes instrumental and
observational effects. These limitations might be harmful for subsequent
scientific applications in astrophysics. Therefore, we aim to develop methods
for using unpaired images and preserving noise characteristics in image
translation. In this work, we propose a two-way image translation model using
GANs that exploits both paired and unpaired images in a semi-supervised manner,
and introduce a noise emulating module that is able to learn and reconstruct
noise characterized by high-frequency features. By experimenting on multi-band
galaxy images from the Sloan Digital Sky Survey (SDSS) and the Canada France
Hawaii Telescope Legacy Survey (CFHT), we show that our method recovers global
and local properties effectively and outperforms benchmark image translation
models. To our best knowledge, this work is the first attempt to apply
semi-supervised methods and noise reconstruction techniques in astrophysical
studies.

7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
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The categories of this paper are: hep-ex
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The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc