Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SimPatch: A Nearest Neighbor Similarity Match between Image Patches   Measuring the similarity between patches in images is a fundamental building
block in various tasks. Naturally, the patch-size has a major impact on the
matching quality, and on the consequent application performance. We try to use
large patches instead of relatively small patches so that each patch contains
more information. We use different feature extraction mechanisms to extract the
features of each individual image patches which forms a feature matrix and find
out the nearest neighbor patches in the image. The nearest patches are
calculated using two different nearest neighbor algorithms in this paper for a
query patch for a given image and the results have been demonstrated in this
paper.

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The categories of this paper are: atom-ph
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The categories of this paper are: hep-th
16
The categories of this paper are: stat
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The categories of this paper are: comp-gas
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The categories of this paper are: mtrl-th
0
The categories of this paper are: hep-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: econ
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: eess
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The categories of this paper are: ao-sci
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The categories of this paper are: cmp-lg