Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Color and Shape Content Based Image Classification using RBF Network and
  PSO Technique: A Survey   The improvement of the accuracy of image query retrieval used image
classification technique. Image classification is well known technique of
supervised learning. The improved method of image classification increases the
working efficiency of image query retrieval. For the improvements of
classification technique we used RBF neural network function for better
prediction of feature used in image retrieval.Colour content is represented by
pixel values in image classification using radial base function(RBF) technique.
This approach provides better result compare to SVM technique in image
representation.Image is represented by matrix though RBF using pixel values of
colour intensity of image. Firstly we using RGB colour model. In this colour
model we use red, green and blue colour intensity values in matrix.SVM with
partical swarm optimization for image classification is implemented in content
of images which provide better Results based on the proposed approach are found
encouraging in terms of color image classification accuracy.

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The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-th
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The categories of this paper are: acc-phys
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The categories of this paper are: atom-ph
3
The categories of this paper are: physics
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The categories of this paper are: funct-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: solv-int
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The categories of this paper are: supr-con