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- W2371730816 abstract "In order to bridge the semantic gap,a multi-modal image retrieval system is proposed based on semantic learning.The system combines three query modes to retrieval images.The paradigm of query by visual feature ranks images by feature extraction and similarity matching;The paradigm of query by label is based on automatic image annotation,but its generalization ability is not good outside the semantic space;The paradigm of Query by Semantic Example(QBSE) can overcome the problem to a great extent.It makes the retrieval more agreeable with human perception by executing the query in either explicit or implicit semantic space.Experimental results show that the paradigm of query by semantic example has higher precision and recall rate than image retrieval based on the texture feature." @default.
- W2371730816 created "2016-06-24" @default.
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- W2371730816 date "2013-01-01" @default.
- W2371730816 modified "2023-09-23" @default.
- W2371730816 title "Multi-modal Image Retrieval Based on Semantic Learning" @default.
- W2371730816 hasPublicationYear "2013" @default.
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