Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Training on Art Composition Attributes to Influence CycleGAN Art
  Generation   I consider how to influence CycleGAN, image-to-image translation, by using
additional constraints from a neural network trained on art composition
attributes. I show how I trained the the Art Composition Attributes Network
(ACAN) by incorporating domain knowledge based on the rules of art evaluation
and the result of applying each art composition attribute to apple2orange image
translation.

0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio