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- W2080704384 abstract "Focusing on the issues of lacking of semantic description on image identification and methods of mapping from low-level semantics to high-level semantics, this paper describes the experiments of identification of image semantic information by using LDA model, which can achieve the mapping from image visual feature to high-level semantics, and experiments on the data sets of Corel 5k and Corel 30k. The experiments test and verify that LDA model performs a good stability on identification of image semantic information, and advantageous on dimension accuracy and recall rate, which provide a new solution and an embodiment of the identifying of image semantics intelligently and automatically." @default.
- W2080704384 created "2016-06-24" @default.
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- W2080704384 date "2013-09-12" @default.
- W2080704384 modified "2023-09-27" @default.
- W2080704384 title "Research on Image Semantic Information Mining Based On Latent Dirichlet Allocation Model" @default.
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- W2080704384 doi "https://doi.org/10.4304/jsw.8.9.2329-2335" @default.
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