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- W1991378166 abstract "This paper presents a Multiple-Instance Decision Based Neural Networks (MI-DBNN) based image retrieval system. Without precisely image segmentation, the image retrieval problem is considered as a Multiple-Instance Learning problem. A set of exemplar images are selected, each of which is labelled as conceptual related (positive) or conceptual unrelated (negative) image. Then, the MI-DBNN is trained to learn the user's preferred image concept from the positive and negative examples. The proposed system is built and located on http://210.240.226.146/MIL/. Experimental results show that our method can significantly improve the retrieving performance from 68.4% to 80.7%, which outperforms to the results of some leading image retrieval methods." @default.
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- W1991378166 date "2012-07-01" @default.
- W1991378166 modified "2023-09-26" @default.
- W1991378166 title "Content based image retrieval using Multiple Instance Decision Based Neural Networks" @default.
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- W1991378166 doi "https://doi.org/10.1109/cyberneticscom.2012.6381641" @default.
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