Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Using Convolutional Neural Networks in Robots with Limited Computational
  Resources: Detecting NAO Robots while Playing Soccer   The main goal of this paper is to analyze the general problem of using
Convolutional Neural Networks (CNNs) in robots with limited computational
capabilities, and to propose general design guidelines for their use. In
addition, two different CNN based NAO robot detectors that are able to run in
real-time while playing soccer are proposed. One of the detectors is based on
the XNOR-Net and the other on the SqueezeNet. Each detector is able to process
a robot object-proposal in ~1ms, with an average number of 1.5 proposals per
frame obtained by the upper camera of the NAO. The obtained detection rate is
~97%.

16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
5
The categories of this paper are: gr-qc
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics