The final publication is available via <a href="https://doi.org/10.1109/ICDAR.2017.222" target="_blank">https://doi.org/10.1109/ICDAR.2017.222</a>.
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dc.description.abstract
The cBAD competition aims at benchmarking state-of-the-art baseline detection algorithms. It is in line with previous competitions such as the ICDAR 2013 Handwriting Segmentation Contest. A new, challenging, dataset was created to test the behavior of state-of-the-art systems on real world data. Since traditional evaluation schemes are not applicable to the size and modality of this dataset, we present a new one that introduces baselines to measure performance. We received submissions from five different teams for both tracks.
en
dc.description.sponsorship
European Union's Horizon 2020
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dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
cBAD
en
dc.subject
baseline detection
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dc.subject
text-line detection
en
dc.title
cBAD: ICDAR2017 Competition on Baseline Detection
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Urheberrechtsschutz
de
dc.rights.license
In Copyright
en
dc.relation.publication
2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)
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dc.relation.isbn
9781538635865
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dc.relation.grantno
674943
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dc.rights.holder
2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
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dc.type.category
Full-Paper Contribution
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tuw.relation.publisher
Kyoto, Japan
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tuw.version
smur
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tuw.publication.orgunit
E193 - Institut für Rechnergestützte Automation
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tuw.publisher.doi
10.1109/ICDAR.2017.222
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dc.identifier.libraryid
AC11365321
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dc.identifier.urn
urn:nbn:at:at-ubtuw:3-3384
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tuw.author.orcid
0000-0002-5048-5128
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tuw.author.orcid
0000-0001-8351-5066
-
tuw.author.orcid
0000-0001-5033-6723
-
dc.rights.identifier
Urheberrechtsschutz
de
dc.rights.identifier
In Copyright
en
item.openaccessfulltext
Open Access
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.grantfulltext
open
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item.languageiso639-1
en
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item.openairetype
conference paper
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item.fulltext
with Fulltext
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item.cerifentitytype
Publications
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crisitem.author.dept
E193-01 - Forschungsbereich Computer Vision
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crisitem.author.dept
E193-01 - Forschungsbereich Computer Vision
-
crisitem.author.dept
E193-01 - Forschungsbereich Computer Vision
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crisitem.author.orcid
0000-0002-5048-5128
-
crisitem.author.orcid
0000-0001-8351-5066
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
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crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology
-
crisitem.author.parentorg
E193 - Institut für Visual Computing and Human-Centered Technology