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مجله بین المللی بینایی کامپیوتر 2013
جزئیات رویداد
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  • making a shallow network deep: conversion of a boosting classifier into a decision tree by boolean optimisation

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    • تاریخ ارائه: 1392/07/24
    • تاریخ انتشار در تی پی بین: 1392/07/24
    • تعداد بازدید: 1044
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     this paper presents a novel way to speed up the evaluation time of a boosting classifier. we make a shallow (flat) network deep (hierarchical) by growing a tree from decision regions of a given boosting classifier. the tree provides many short paths for speeding up while preserving the reasonably smooth decision regions of the boosting classifier for good generalisation. for converting a boosting classifier into a decision tree, we formulate a boolean optimisation problem, which has been previously studied for circuit design but limited to a small number of binary variables. in this work, a novel optimisation method is proposed for, firstly, several tens of variables i.e. weak-learners of a boosting classifier, and then any larger number of weak-learners by using a two-stage cascade. experiments on the synthetic and face image data sets show that the obtained tree achieves a significant speed up both over a standard boosting classifier and the fast-exit—a previously described method for speeding-up boosting classification, at the same accuracy. the proposed method as a general meta-algorithm is also useful for a boosting cascade, where it speeds up individual stage classifiers by different gains. the proposed method is further demonstrated for fast-moving object tracking and segmentation problems.

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