Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with
  MDLSTM Attention   We present an attention-based model for end-to-end handwriting recognition.
Our system does not require any segmentation of the input paragraph. The model
is inspired by the differentiable attention models presented recently for
speech recognition, image captioning or translation. The main difference is the
covert and overt attention, implemented as a multi-dimensional LSTM network.
Our principal contribution towards handwriting recognition lies in the
automatic transcription without a prior segmentation into lines, which was
crucial in previous approaches. To the best of our knowledge this is the first
successful attempt of end-to-end multi-line handwriting recognition. We carried
out experiments on the well-known IAM Database. The results are encouraging and
bring hope to perform full paragraph transcription in the near future.

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The categories of this paper are: hep-ph
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The categories of this paper are: nlin
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
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The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
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The categories of this paper are: math-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: chao-dyn
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The categories of this paper are: atom-ph
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The categories of this paper are: adap-org
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The categories of this paper are: quant-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: comp-gas