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Efficient decision tree traversal in an adaptive boosting (AdaBoost) classifier
Efficient decision tree traversal in an adaptive boosting (AdaBoost) classifier
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机译:自适应提升(AdaBoost)分类器中的有效决策树遍历
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摘要
A method for object classification in a decision tree based adaptive boosting (AdaBoost) classifier implemented on a single-instruction multiple-data (SIMD) processor is provided that includes receiving feature vectors extracted from N consecutive window positions in an image in a memory coupled to the SIMD processor and evaluating the N consecutive window positions concurrently by the AdaBoost classifier using the feature vectors and vector instructions of the SIMD processor, in which the AdaBoost classifier concurrently traverses decision trees for the N consecutive window positions until classification is complete for the N consecutive window positions.
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