Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Model Adaption Object Detection System for Robot   Object detection for robot guidance is a crucial mission for autonomous
robots, which has provoked extensive attention for researchers. However, the
changing view of robot movement and limited available data hinder the research
in this area. To address these matters, we proposed a new vision system for
robots, the model adaptation object detection system. Instead of using a single
one to solve problems, We made use of different object detection neural
networks to guide the robot in accordance with various situations, with the
help of a meta neural network to allocate the object detection neural networks.
Furthermore, taking advantage of transfer learning technology and depthwise
separable convolutions, our model is easy to train and can address small
dataset problems.

36
The categories of this paper are: cmp-lg
17
The categories of this paper are: q-fin
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat