Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/7160
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dc.contributor.authorChammas, Michelen_US
dc.contributor.authorMakhoul, Abdallahen_US
dc.contributor.authorDemerjian, Jacquesen_US
dc.contributor.authorDannaoui, Elieen_US
dc.date.accessioned2024-01-12T07:12:33Z-
dc.date.available2024-01-12T07:12:33Z-
dc.date.issued2024-12-06-
dc.identifier.issn13807501-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/7160-
dc.description.abstractThe extraction of paleographical features is an important task to study the identity of the text in the Historical Manuscripts. One of the major features is the identification of the writer or copyist. Many researchers have worked on an automated system for writer identification, and with the development of deep learning techniques many approaches have been proposed. Most of the previous studies have developed a multi-steps system, while very few of them performed an End-to-End approach. Most of the systems rely on a pre-processing step to prepare the data in order to facilitate recognition. This paper presents an End-to-End deep learning system for writer identification, tested on four different datasets: ICDAR19 and ICFHR20 (Latin datasets), KHATT and Balamand (Arabic datasets). The system is based on the Deep-TEN approach using a customized ResNet-50 network for features and local descriptor extraction with an integration of a NetVLAD end-layer to compute and encode the global descriptor. It was compared with our state-of-the-art system, winner of ICFHR20 HisFrag competition, and showed an interesting performance on all datasets without any pre-processing techniques.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.subjectWriter identificationen_US
dc.subjecthistorical documentsen_US
dc.subjectDeep learningen_US
dc.subjectDocument Analysisen_US
dc.subjectEnd-to-enden_US
dc.subjectArabic manuscriptsen_US
dc.titleAn End-to-End deep learning system for writer identification in handwritten Arabic manuscriptsen_US
dc.typeJournal Articleen_US
dc.identifier.doihttps://doi.org/10.1007/s11042-023-17303-8-
dc.identifier.scopus2-s2.0-85178879423-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85178879423-
dc.contributor.affiliationDepartment of Computer Scienceen_US
dc.contributor.affiliationInstitute of History Archeology and Near Eastern Studiesen_US
dc.description.volume83en_US
dc.description.issue18en_US
dc.description.startpage54569en_US
dc.description.endpage54589en_US
dc.date.catalogued2024-06-27-
dc.description.statusPublisheden_US
dc.identifier.openURLhttps://link.springer.com/article/10.1007/s11042-023-17303-8en_US
dc.relation.ispartoftextMultimedia Tools and Applicationsen_US
crisitem.author.parentorgFaculty of Arts and Sciences-
Appears in Collections:Institute of History Archeology and Near Eastern Studies
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