完整後設資料紀錄
DC 欄位語言
dc.contributor.authorChang, Feng-Chengen_US
dc.contributor.authorHang, Hsueh-Mingen_US
dc.date.accessioned2014-12-08T15:16:37Z-
dc.date.available2014-12-08T15:16:37Z-
dc.date.issued2006-05-01en_US
dc.identifier.issn0916-8532en_US
dc.identifier.urihttp://dx.doi.org/10.1093/ietisy/e89-d.5.1720en_US
dc.identifier.urihttp://hdl.handle.net/11536/12266-
dc.description.abstractContent-based image search has long been considered a difficult task. Making correct conjectures on the user intention (perception) based on the query images is a critical step in the content-based search. One key concept in this paper is how we find the user preferred low-level image characteristics from the multiple positive samples provided by the user. The second key concept is how we generate a set of consistent "pseudo images" when the user does not provide a sufficient number of samples. The notion of image feature stability is thus introduced. The third key concept is how we use negative images as pruning criterion. In realizing the preceding concepts, an image search scheme is developed using the weighted lowlevel image features. At the end, quantitative simulation results are used to show the effectiveness of these concepts.en_US
dc.language.isoen_USen_US
dc.subjectimage retrievalen_US
dc.subjectperception weightingen_US
dc.subjectrelevance feedbacken_US
dc.titleA relevance feedback image retrieval scheme using multi-instance and pseudo image conceptsen_US
dc.typeArticleen_US
dc.identifier.doi10.1093/ietisy/e89-d.5.1720en_US
dc.identifier.journalIEICE TRANSACTIONS ON INFORMATION AND SYSTEMSen_US
dc.citation.volumeE89Den_US
dc.citation.issue5en_US
dc.citation.spage1720en_US
dc.citation.epage1731en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000237827000015-
dc.citation.woscount7-
顯示於類別:期刊論文