Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/7009
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dc.contributor.authorTsapatsoulis, Nicolasen
dc.contributor.authorTheodosiou, Zenonas-
dc.contributor.otherΤσαπατσούλης, Νικόλας-
dc.contributor.otherΘεοδοσίου, Ζήνωνας-
dc.date.accessioned2013-02-13T13:53:43Zen
dc.date.accessioned2013-05-17T10:05:01Z-
dc.date.accessioned2015-12-08T09:27:56Z-
dc.date.available2013-02-13T13:53:43Zen
dc.date.available2013-05-17T10:05:01Z-
dc.date.available2015-12-08T09:27:56Z-
dc.date.issued2012en
dc.identifier.citation8th IFIP WG 12.5 international conference, AIAI 2012, Halkidiki, Greece, September 27-30en
dc.identifier.urihttp://ktisis.cut.ac.cy/handle/10488/7009en
dc.description.abstractImage classification arises as an important phase in the overall process of automatic image annotation and image retrieval. Usually, a set of manually annotated images is used to train supervised systems and classify images into classes. The act of crowdsourcing has largely focused on investigating strategies for reducing the time, cost and effort required for the creation of the annotated data. In this paper we experiment with the efficiency of various classifiers in building visual models for keywords through crowdsourcing with the aid of Weka tool and a variety of low-level features. A total number of 500 manually annotated images related to athletics domain are used to build and test 8 visual models. The experimental results have been examined using the classification accuracy and are very promising showing the ability of the visual models to classify the images into the corresponding classes with the highest average classification accuracy of 74.38% in the purpose of SMO data classifieren
dc.formatpdfen
dc.language.isoenen
dc.publisherSpringeren
dc.rights© IFIP International Federation for Information Processingen
dc.subjectArtificial intelligenceen
dc.subjectInformation technologyen
dc.subjectAthleticsen
dc.titleModelling crowdsourcing originated keywords within the athletics domainen
dc.typeConference Papersen
dc.collaborationCyprus University of Technology-
dc.subject.categoryArts-
dc.countryCyprus-
dc.subject.fieldHumanities-
dc.identifier.doi10.1007/978-3-642-33409-2_42en
dc.dept.handle123456789/100en
item.languageiso639-1other-
item.fulltextNo Fulltext-
item.grantfulltextnone-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.orcid0000-0002-6739-8602-
crisitem.author.parentorgFaculty of Communication and Media Studies-
crisitem.author.parentorgFaculty of Communication and Media Studies-
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers
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