Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Laparoscopy Surgery CO2 Removal via Generative Adversary Network and
  Dark Channel Prior   Laparoscopic surgery uses a thin tube with a camera called a laparoscope,
which is inserted into the abdomen through a small incision in the skin during
surgery. This allows to a surgeon to see inside of the body without causing
significant injury to the patient. These characteristics make laparoscopy a
widely used technique. In laparoscopic surgery, image quality can be severely
degraded by surgical smoke caused by the use of tissue dissection tools which
reduces the visibility of the observed organs and tissues. This lack of
visibility increases the possibility of errors and surgery time with the
consequences that this may have on the patient's health. In this paper, we
introduce a novel hybrid approach for computational smoke removal which is
based on the combination of a widely dehazing method used: the dark channel
prior (DCP) and a pixel-to-pixel neural network approach: Generative Adversary
Network (GAN). The experimental results have proven that the proposed method
achieves a better performance than the individual results of the DCP and GAN in
terms of restoration quality, obtaining a PSNR value of 25 and SSIM index of
0.88 over a test set of synthetic images.

2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
1
The categories of this paper are: cs
6
The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
13
The categories of this paper are: quant-ph
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
34
The categories of this paper are: chem-ph
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga