Apport d'informations textuelles pour l'extraction de structures de documents manuscrits
Identifieur interne : 000766 ( France/Analysis ); précédent : 000765; suivant : 000767Apport d'informations textuelles pour l'extraction de structures de documents manuscrits
Auteurs : Florent Montreuil [France] ; Emmanuèle Grosicki [France] ; Stéphane Nicolas [France] ; Laurent Heutte [France]Source :
Descripteurs français
- mix :
Abstract
RÉSUMÉ. Cet article décrit une nouvelle approche utilisant des Champs Aléatoires Conditionnels (CACs) pour extraire la mise en page de documents manuscrits non contraints. De bons résultats ont été obtenus montrant la capacité des approches CACs à extraire la mise en page d'un document complexe. On se propose dans cet article d'étudier l'apport d'une information textuelle dans la modélisation. On compare cette nouvelle approche avec les approches classiques utilisant des informations graphiques et spatiales. ABSTRACT. The paper describes a new approach using Conditional Random Fields (CRFs) to extract layouts in unconstrained handwritten documents. Good results have been reported, showing the capacity of our approach to extract layout on a complex document. We propose in this paper to study the contribution of a textual information in this modelisation. We compare this new approach with classical approach using graphicical and spatial informations
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Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 000406
- to stream Hal, to step Curation: 000406
- to stream Hal, to step Checkpoint: 000445
- to stream Main, to step Merge: 000924
- to stream Main, to step Curation: 000917
- to stream Main, to step Exploration: 000917
- to stream France, to step Extraction: 000766
Links to Exploration step
Hal:hal-00488342Le document en format XML
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Cet article décrit une nouvelle approche utilisant des Champs Aléatoires Conditionnels (CACs) pour extraire la mise en page de documents manuscrits non contraints. De bons résultats ont été obtenus montrant la capacité des approches CACs à extraire la mise en page d'un document complexe. On se propose dans cet article d'étudier l'apport d'une information textuelle dans la modélisation. On compare cette nouvelle approche avec les approches classiques utilisant des informations graphiques et spatiales. ABSTRACT. The paper describes a new approach using Conditional Random Fields (CRFs) to extract layouts in unconstrained handwritten documents. Good results have been reported, showing the capacity of our approach to extract layout on a complex document. We propose in this paper to study the contribution of a textual information in this modelisation. We compare this new approach with classical approach using graphicical and spatial informations</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Haute-Normandie</li><li>Région Normandie</li></region><settlement><li>Le Havre</li><li>Rouen</li></settlement><orgName><li>Université de Rouen</li><li>Université du Havre</li></orgName></list><tree><country name="France"><region name="Région Normandie"><name sortKey="Montreuil, Florent" sort="Montreuil, Florent" uniqKey="Montreuil F" first="Florent" last="Montreuil">Florent Montreuil</name></region><name sortKey="Grosicki, Emmanuele" sort="Grosicki, Emmanuele" uniqKey="Grosicki E" first="Emmanuèle" last="Grosicki">Emmanuèle Grosicki</name><name sortKey="Heutte, Laurent" sort="Heutte, Laurent" uniqKey="Heutte L" first="Laurent" last="Heutte">Laurent Heutte</name><name sortKey="Nicolas, Stephane" sort="Nicolas, Stephane" uniqKey="Nicolas S" first="Stéphane" last="Nicolas">Stéphane Nicolas</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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