Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sequence-to-Label Script Identification for Multilingual OCR   We describe a novel line-level script identification method. Previous work
repurposed an OCR model generating per-character script codes, counted to
obtain line-level script identification. This has two shortcomings. First, as a
sequence-to-sequence model it is more complex than necessary for the
sequence-to-label problem of line script identification. This makes it harder
to train and inefficient to run. Second, the counting heuristic may be
suboptimal compared to a learned model. Therefore we reframe line script
identification as a sequence-to-label problem and solve it using two
components, trained end-toend: Encoder and Summarizer. The encoder converts a
line image into a feature sequence. The summarizer aggregates the sequence to
classify the line. We test various summarizers with identical inception-style
convolutional networks as encoders. Experiments on scanned books and photos
containing 232 languages in 30 scripts show 16% reduction of script
identification error rate compared to the baseline. This improved script
identification reduces the character error rate attributable to script
misidentification by 33%.

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The categories of this paper are: chem-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: patt-sol
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The categories of this paper are: astro-ph
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The categories of this paper are: hep-th
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The categories of this paper are: cond-mat
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The categories of this paper are: comp-gas
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The categories of this paper are: q-alg
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The categories of this paper are: nucl-th
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The categories of this paper are: bayes-an
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The categories of this paper are: mtrl-th
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The categories of this paper are: dg-ga
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The categories of this paper are: alg-geom
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The categories of this paper are: nlin
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The categories of this paper are: cmp-lg
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The categories of this paper are: physics