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- W1589566882 abstract "Learning a hashing function for cross-media search is very desirable due to its low storage cost and fast query speed. However, the data crawled from Internet cannot always guarantee good correspondence among different modalities which affects the learning for hashing function. In this paper, we focus on cross-modal hashing with partially corresponded data. The data without full correspondence are made in use to enhance the hashing performance. The experiments on Wiki and NUS-WIDE datasets demonstrates that the proposed method outperforms some state-of-the-art hashing approaches with fewer correspondence information." @default.
- W1589566882 created "2016-06-24" @default.
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- W1589566882 date "2015-02-18" @default.
- W1589566882 modified "2023-09-27" @default.
- W1589566882 title "Cross-Modality Hashing with Partial Correspondence" @default.
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- W1589566882 doi "https://doi.org/10.48550/arxiv.1502.05224" @default.
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