Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Analyzing First-Person Stories Based on Socializing, Eating and
  Sedentary Patterns   First-person stories can be analyzed by means of egocentric pictures acquired
throughout the whole active day with wearable cameras. This manuscript presents
an egocentric dataset with more than 45,000 pictures from four people in
different environments such as working or studying. All the images were
manually labeled to identify three patterns of interest regarding people's
lifestyle: socializing, eating and sedentary. Additionally, two different
approaches are proposed to classify egocentric images into one of the 12 target
categories defined to characterize these three patterns. The approaches are
based on machine learning and deep learning techniques, including traditional
classifiers and state-of-art convolutional neural networks. The experimental
results obtained when applying these methods to the egocentric dataset
demonstrated their adequacy for the problem at hand.

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The categories of this paper are: econ
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The categories of this paper are: atom-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-lat
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The categories of this paper are: alg-geom
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The categories of this paper are: q-fin
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The categories of this paper are: gr-qc
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The categories of this paper are: acc-phys
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The categories of this paper are: plasm-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: adap-org
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The categories of this paper are: supr-con
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The categories of this paper are: chao-dyn
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The categories of this paper are: solv-int