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In this article, a bottom-up text localization technique is proposed that detects and extracts homogeneous text from document images.
This article proposes a new bottom-up method which detects and extracts homogeneous text in document images indifferent to font types and size by using connected components analysis for the object detection, document structure elements (DSE) to construct a descriptor and SVM to tag the appropriate objects as text.
So that while they do not compose a homogeneous text, held together by the rhetorical power of a narrative voice, and in fact are anything but homogeneous, these texts bear the presence of the editor in these discrete marks and indications.
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In 2011, Chiang et al. [30] proposed a general text recognition technique to handle non-homogeneous text by exploiting dynamic character grouping criteria based on the character sizes and maximum desired string curvature.
Because of the existence of a common and relatively homogeneous philosophical background—Hebrew texts were much less numerous and less diverse than Arabic philosophical works—and the fact that Jewish philosophers reading and writing in Hebrew read the works of their contemporaries and immediate predecessors, something like a dialogue can be discerned.
Pooled statistics are reported within the text only for statistically homogeneous data sets.
The result is something akin to my digital stream of consciousness, consisting of a homogeneous flow of status updates, links of interest, pictures, text, quotes, conversations and practically anything else that crosses my path during the day.
We further assumed that each of these organs was separately made up of homogeneous cell populations with identical signaling dynamics with minor differences (see Supplementary Text S1 and S2).
The log estimated to billed texts (Pearson's r 0.78 p<0.01) revealed a large, but homogeneous, variance of the residuals of log-to-log regression (random error).
We extracted 1,584 mutation mentions from 1,771 full text articles, for 1,273 residues in 3,908 fragments (145 fragments from homogeneous clusters and remaining from heterogeneous clusters).
However, a large variability was also observed within the group of European languages, which were homogeneous in terms of styles, consisting mostly of literature and some technical texts.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com