k nearest neighbor and Bayesian classifications shortcomings which are long training time
complicated programming and operation
bad real-time performance. In this paper
the video vehicle classification algorithm based on C4.5 decision trees is proposed
the design method of the hierarchical classifier is introduced
and the construction process of C4.5 decision trees as an example which was used to divide light-duty vehicle into minibus and van is introduced in detail. Finally
the experimental results demonstrate the effectiveness of the video vehicle classification algorithm based on C4.5 decision trees.
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references
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