Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Weakly Supervised Learning Guided by Activation Mapping Applied to a
  Novel Citrus Pest Benchmark   Pests and diseases are relevant factors for production losses in agriculture
and, therefore, promote a huge investment in the prevention and detection of
its causative agents. In many countries, Integrated Pest Management is the most
widely used process to prevent and mitigate the damages caused by pests and
diseases in citrus crops. However, its results are credited by humans who
visually inspect the orchards in order to identify the disease symptoms,
insects and mite pests. In this context, we design a weakly supervised learning
process guided by saliency maps to automatically select regions of interest in
the images, significantly reducing the annotation task. In addition, we create
a large citrus pest benchmark composed of positive samples (six classes of mite
species) and negative samples. Experiments conducted on two large datasets
demonstrate that our results are very promising for the problem of pest and
disease classification in the agriculture field.

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The categories of this paper are: patt-sol
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The categories of this paper are: nucl-th
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The categories of this paper are: stat
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The categories of this paper are: atom-ph
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The categories of this paper are: nlin
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The categories of this paper are: eess
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
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The categories of this paper are: chao-dyn
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The categories of this paper are: math-ph
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
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The categories of this paper are: alg-geom
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The categories of this paper are: solv-int
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The categories of this paper are: q-fin
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The categories of this paper are: supr-con