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X-WR-CALNAME;VALUE=TEXT:Eventi DIAG
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TZID:Europe/Paris
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DTSTART:20191027T030000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
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DTSTART:20200329T020000
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UID:calendar.19545.field_data.0@www.glad.uniroma1.it
DTSTAMP:20260406T193346Z
CREATED:20200302T095756Z
DESCRIPTION:Digital preservation of written cultural heritage is a fundamen
 tal topic in digital humanities. This task is hard because of the state of
  preservation of the document and by the lack of typographic standards. In
  this seminar Dr. Zahra Ziran (Università degli Studi di Firenze) describe
 s a technique for transcript alignment in early printed books.\n\nThe tech
 nique is based on deep models in combination with dynamic programming algo
 rithms. Two object detection models\, based on Faster R-CNN\, are trained 
 to locate words. An initial model is first trained to recognize generic wo
 rds and hyphens by using information about the number of words in text lin
 es. Using the model prediction on pages where a line-by-line ground-truth 
 annotation is available\, a second model able to detect landmark words is 
 trained. The alignment is then based on the identification of landmark wor
 ds in pages where we only know the text corresponding to zones on the page
 .\n\nThe proposed technique is evaluated on publicly available digitizatio
 n of the Gutenberg Bible while the transcription is based on the Vulgata\,
  a late 4-th century Latin translation of the Bible.
DTSTART;TZID=Europe/Paris:20200309T150000
DTEND;TZID=Europe/Paris:20200309T170000
LAST-MODIFIED:20200302T125947Z
LOCATION:Room B203 DIAG
SUMMARY:Text alignment in early printed books combining deep learning and d
 ynamic programming - Zahra Ziran (Università degli Studi di Firenze)
URL;TYPE=URI:http://www.glad.uniroma1.it/node/19545
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