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- W2582529176 abstract "With the technical advances, multimedia data is growing exponentially. It is progressively vital to mine the information from a video database consequently. Finding association between things in a large video assumes an extensive part in the video information mining. In light of the innovative work in the previous years, use of association mining is developing in various areas, for example, surveillance, sports, news, documents, motion pictures, and individual and online media accumulations. This paper provides a general framework of mining the association rules from video surveillance data. Our approach will provide semantic content extraction from surveillance videos using video association mining." @default.
- W2582529176 created "2017-02-03" @default.
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- W2582529176 date "2016-05-01" @default.
- W2582529176 modified "2023-09-27" @default.
- W2582529176 title "Mining semantic content using association rules in video surveillance" @default.
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- W2582529176 doi "https://doi.org/10.1109/icaccct.2016.7831731" @default.
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