Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An application of a pseudo-parabolic modeling to texture image
  recognition   In this work, we present a novel methodology for texture image recognition
using a partial differential equation modeling. More specifically, we employ
the pseudo-parabolic Buckley-Leverett equation to provide a dynamics to the
digital image representation and collect local descriptors from those images
evolving in time. For the local descriptors we employ the magnitude and signal
binary patterns and a simple histogram of these features was capable of
achieving promising results in a classification task. We compare the accuracy
over well established benchmark texture databases and the results demonstrate
competitiveness, even with the most modern deep learning approaches. The
achieved results open space for future investigation on this type of modeling
for image analysis, especially when there is no large amount of data for
training deep learning models and therefore model-based approaches arise as
suitable alternatives.

15
The categories of this paper are: nucl-ex
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
9
The categories of this paper are: nlin
21
The categories of this paper are: adap-org
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg