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- W2374388947 abstract "The problems in the content-based image retrieval are analyzed,and then the ontology theory method is used to build the low-level feature ontology of the image and the special image ontology.Meanwhile,the concept of image descriptor is defined and corresponding image combination rules are setup.At last,the low-level features are selected to retrieve the images,and the multi-class support vector machine(SVM) is chosen to achieve the conjunction between the low-level feature and the high-level description information.Then the semantic retrieval is realized and the influence of the semantic gap problem on the content based image retrieval is reduced.The experiment results show that this model can enhance the precision in content based image retrieval,and it can achieve the semantic retrieval by 3～5 times of feedback." @default.
- W2374388947 created "2016-06-24" @default.
- W2374388947 creator A5003260108 @default.
- W2374388947 date "2012-01-01" @default.
- W2374388947 modified "2023-09-23" @default.
- W2374388947 title "A New Model of Content Image Retrieval Based on the Ontology Theory Description" @default.
- W2374388947 hasPublicationYear "2012" @default.
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