tech,42-1-N03-1018,bq |
In this paper , we introduce a
<term>
generative probabilistic optical character recognition ( OCR ) model
</term>
that describes an end-to-end process in the
<term>
noisy channel framework
</term>
, progressing from generation of
<term>
true text
</term>
through its transformation into the
<term>
noisy output
</term>
of an
<term>
OCR system
</term>
.
|
#2709
In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system . |
tech,7-2-N03-1018,bq |
The
<term>
model
</term>
is designed for use in
<term>
error correction
</term>
, with a focus on
<term>
post-processing
</term>
the
<term>
output
</term>
of black-box
<term>
OCR systems
</term>
in order to make it more useful for
<term>
NLP tasks
</term>
.
|
#2719
The model is designed for use in error correction , with a focus on post-processing the output of black-box OCR systems in order to make it more useful for NLP tasks. |