A Fast Annotation Model Based on Visual Concept Distribution
2013 ◽
Vol 333-335
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pp. 988-991
Keyword(s):
Image annotation is one of the important technologies in image retrieval and semantic analysis. To overcome the estimation and efficiency problem in CMRM model, we proposed a Visual Concept Distribution based annotation model which estimates the probability through the Visual Concept Set. Experiment results shows that our approach outperforms three classical annotation models (CMRM, CRM and PLSA-WORDS) and closes to the complicated PLSA-FUSION model.
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2021 ◽
Vol 31
(4)
◽
pp. 688-698
2015 ◽
Vol 9
(4)
◽
Keyword(s):
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2020 ◽
Vol 93
◽
pp. 103686
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