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Web image retrieval refinement by visual contents
Gong Z.; Liu Q.; Zhang J.
Conference Name7th International Conference on Web-Age Information Management
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4016 LNCS
Conference DateJUN 17-19, 2006
Conference PlaceHong Kong, PEOPLES R CHINA

For Web image retrieval, two basic methods can be used for representing and indexing Web images. One is based on the associate text around the Web images; and the other utilizes visual features of images, such as color, texture, shape, as the descriptions of Web images. However, those two methods are often applied independently in practice. In fact, both have their limitations to support Web image retrieval. This paper proposes a novel model called 'multiplied refinement', which is more applicable to combination of those two basic methods. Our experiments compare three integration models, including multiplied refinement model, linear refinement model and expansion model, and show that the proposed model yields very good performance. © Springer-Verlag Berlin Heidelberg 2006.

URLView the original
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000239658700012
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Citation statistics
Document TypeConference paper
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Gong Z.,Liu Q.,Zhang J.. Web image retrieval refinement by visual contents[C],2006:134-145.
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