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• W1967732418 abstract "Large-scale recognition problems with thousands of classes pose a particular challenge because applying the classifier requires more computation as the number of classes grows. The label tree model integrates classification with the traversal of the tree so that complexity grows logarithmically. In this paper, we show how the parameters of the label tree can be found using maximum likelihood estimation. This new probabilistic learning technique produces a label tree with significantly improved recognition accuracy." @default.
• W1967732418 created "2016-06-24" @default.
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• W1967732418 date "2013-06-01" @default.
• W1967732418 modified "2023-10-17" @default.
• W1967732418 title "Probabilistic Label Trees for Efficient Large Scale Image Classification" @default.
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• W1967732418 doi "https://doi.org/10.1109/cvpr.2013.114" @default.
• W1967732418 hasPublicationYear "2013" @default.
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