Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Feathers dataset for Fine-Grained Visual Categorization   This paper introduces a novel dataset FeatherV1, containing 28,272 images of
feathers categorized by 595 bird species. It was created to perform taxonomic
identification of bird species by a single feather, which can be applied in
amateur and professional ornithology. FeatherV1 is the first publicly available
bird's plumage dataset for machine learning, and it can raise interest for a
new task in fine-grained visual recognition domain. The latest version of the
dataset can be downloaded at
https://github.com/feathers-dataset/feathersv1-dataset. We also present
feathers classification task results. We selected several deep learning
architectures (DenseNet based) for categorical crossentropy values comparison
on the provided dataset.

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The categories of this paper are: q-alg
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The categories of this paper are: hep-ph
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The categories of this paper are: nlin
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The categories of this paper are: astro-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: patt-sol
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The categories of this paper are: nucl-ex
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The categories of this paper are: gr-qc
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The categories of this paper are: nucl-th
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The categories of this paper are: econ
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The categories of this paper are: stat
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The categories of this paper are: cond-mat
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The categories of this paper are: plasm-ph
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The categories of this paper are: math
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The categories of this paper are: bayes-an
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The categories of this paper are: funct-an