Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reinforcement Learning for Improving Object Detection   The performance of a trained object detection neural network depends a lot on
the image quality. Generally, images are pre-processed before feeding them into
the neural network and domain knowledge about the image dataset is used to
choose the pre-processing techniques. In this paper, we introduce an algorithm
called ObjectRL to choose the amount of a particular pre-processing to be
applied to improve the object detection performances of pre-trained networks.
The main motivation for ObjectRL is that an image which looks good to a human
eye may not necessarily be the optimal one for a pre-trained object detector to
detect objects.

6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
13
The categories of this paper are: quant-ph
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
14
The categories of this paper are: math-ph
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con