Show simple item record

dc.contributor.authorVirga, P.en_US
dc.contributor.authorDuygulu, P.en_US
dc.date.accessioned2016-02-08T11:51:42Z
dc.date.available2016-02-08T11:51:42Zen_US
dc.date.issued2005en_US
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11693/27375en_US
dc.description.abstractIn this study, we present a systematic evaluation of machine translation methods applied to the image annotation problem. We used the well-studied Corel data set and the broadcast news videos used by TRECVID 2003 as our dataset. We experimented with different models of machine translation with different parameters. The results showed that the simplest model produces the best performance. Based on this experience, we also proposed a new method, based on cross-lingual information retrieval techniques, and obtained a better retrieval performance.en_US
dc.language.isoEnglishen_US
dc.source.titleLecture Notes in Computer Scienceen_US
dc.relation.isversionofhttps://doi.org/10.1007/11526346_21en_US
dc.subjectMathematical modelsen_US
dc.subjectProblem solvingen_US
dc.subjectCross-lingual information retrievalen_US
dc.subjectImage annotationen_US
dc.subjectMachine translation methodsen_US
dc.subjectImage retrievalen_US
dc.titleSystematic evaluation of machine translation methods for image and video annotationen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.citation.spage174en_US
dc.citation.epage183en_US
dc.citation.volumeNumber3568en_US
dc.identifier.doi10.1007/11526346_21en_US
dc.publisherSpringeren_US
dc.identifier.eissn1611-3349en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record