Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transfer Learning for OCRopus Model Training on Early Printed Books   A method is presented that significantly reduces the character error rates
for OCR text obtained from OCRopus models trained on early printed books when
only small amounts of diplomatic transcriptions are available. This is achieved
by building from already existing models during training instead of starting
from scratch. To overcome the discrepancies between the set of characters of
the pretrained model and the additional ground truth the OCRopus code is
adapted to allow for alphabet expansion or reduction. The character set is now
capable of flexibly adding and deleting characters from the pretrained alphabet
when an existing model is loaded. For our experiments we use a self-trained
mixed model on early Latin prints and the two standard OCRopus models on modern
English and German Fraktur texts. The evaluation on seven early printed books
showed that training from the Latin mixed model reduces the average amount of
errors by 43% and 26%, respectively compared to training from scratch with 60
and 150 lines of ground truth, respectively. Furthermore, it is shown that even
building from mixed models trained on data unrelated to the newly added
training and test data can lead to significantly improved recognition results.

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The categories of this paper are: math-ph
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The categories of this paper are: nlin
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The categories of this paper are: chem-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ph
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The categories of this paper are: supr-con
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The categories of this paper are: quant-ph
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The categories of this paper are: q-fin
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The categories of this paper are: patt-sol
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The categories of this paper are: q-alg
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The categories of this paper are: solv-int
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The categories of this paper are: math
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The categories of this paper are: physics
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The categories of this paper are: acc-phys