Text Line Segmentation in Historical Newspapers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43968531" target="_blank" >RIV/49777513:23520/22:43968531 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-23480-4_3" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-23480-4_3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-23480-4_3" target="_blank" >10.1007/978-3-031-23480-4_3</a>
Alternative languages
Result language
angličtina
Original language name
Text Line Segmentation in Historical Newspapers
Original language description
The paper deals with text line segmentation in historical newspapers. We propose a novel approach which decomposes this problem into two steps: text-block and text-line segmentation. The method should solve issues that may appear in a more commonly used one-step approach. The particular tasks are handled using fully convolutional neural networks. The approach is evaluated on two standard corpora, Europeana and RDCL 2019, and on a novel dataset created from data available in Porta fontium portal. This dataset is freely available for research purposes.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF17_048%2F0007267" target="_blank" >EF17_048/0007267: Research and Development of Intelligent Components of Advanced Technologies for the Pilsen Metropolitan Area (InteCom)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence and Soft Computing
ISBN
978-3-031-23479-8
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
14
Pages from-to
35-48
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Zakopane, Polsko
Event date
Jun 19, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000972697500003