@Book{1662425813,
author="Gr{\"u}ning, Tobias",
title="Neural text line extraction in historical documents: a two-stage clustering approach",
year="2018",
address="Rostock",
abstract="Accessibility of the valuable cultural heritage which is hidden in countless scanned historical documents is the motivation for the presented dissertation. The developed (fully automatic) text line extraction methodology combines state-of-the-art machine learning techniques and modern image processing methods. It demonstrates its quality by outperforming several other approaches on a couple of benchmarking datasets. The method is already being used by a wide audience of researchers from different disciplines and thus contributes its (small) part to the aforementioned goal.<eng>",
school="Universit{\"a}t Rostock",
note="vorgelegt von Tobias Gr{\"u}ning",
note="GutachterInnen: Roger Labahn (Universit{\"a}t Rostock, Institut f{\"u}r Mathematik) ; Basilis Gatos (Institute of Informatics and Telecommunications, National Center for Scientific Research ``Demokritos'')",
note="Dissertation Universit{\"a}t Rostock 2019",
doi="10.18453/rosdok_id00002427",
url="http://purl.uni-rostock.de/rosdok/id00002427",
url="https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00002427-7",
url="https://d-nb.info/1293655813/34",
url="https://doi.org/10.18453/rosdok_id00002427",
language="English"
}