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The Optimal pedestrian detection algorithm based on dynamic adaptive region convolution model

机译:基于动态自适应区域卷积模型的最优行人检测算法

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The traditional target detection and identification algorithm is difficult to adapt to the massive data. And the expression of the method it relies on is designed by means of manual, which is not only very time-consuming, but also very dependence for professional knowledge and data itself. Aiming at the problem of pedestrian detection in complex environment, a pedestrian detection algorithm based on dynamic adaptive region convolution model is proposed. The detection results on INRIA pedestrian data set show the improved detection performance. And the proposed method can detect pedestrians successfully in most complex background.
机译:传统的目标检测与识别算法难以适应海量数据。并且它所依赖的方法的表达是通过手动方式设计的,这不仅非常耗时,而且非常依赖专业知识和数据本身。针对复杂环境下的行人检测问题,提出了一种基于动态自适应区域卷积模型的行人检测算法。 INRIA行人数据集的检测结果显示出改进的检测性能。所提方法可以在最复杂的背景下成功检测出行人。

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