Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: License Plate Recognition with Compressive Sensing Based Feature
  Extraction   License plate recognition is the key component to many automatic traffic
control systems. It enables the automatic identification of vehicles in many
applications. Such systems must be able to identify vehicles from images taken
in various conditions including low light, rain, snow, etc. In order to reduce
the complexity and cost of the hardware required for such devices, the
algorithm should be as efficient as possible. This paper proposes a license
plate recognition system which uses a new approach based on compressive sensing
techniques for dimensionality reduction and feature extraction. Dimensionality
reduction will enable precise classification with less training data while
demanding less computational power. Based on the extracted features, character
recognition and classification is done by a Support Vector Machine classifier.

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The categories of this paper are: alg-geom
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The categories of this paper are: comp-gas
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The categories of this paper are: math-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
18
The categories of this paper are: econ
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The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
6
The categories of this paper are: astro-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-ph
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The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con