Data Distillation for Traffic Sign Detection

A. Popov, V. Shakhuro, A. Konushin
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引用次数: 1

Abstract

This work is devoted to the traffic sign detection on images using deep learning methods. We focus on the problem of detector transfer to new datasets with different road signs. We present an algorithm for distilling a set of unlabelled data to select the most informative images to be labeled. This method allows to significantly reduce the amount of data labeling with a small decline of detector performance.
用于交通标志检测的数据蒸馏
本工作致力于使用深度学习方法对图像进行交通标志检测。我们专注于检测器转移到具有不同道路标志的新数据集的问题。我们提出了一种算法,用于提取一组未标记的数据,以选择最具信息量的图像进行标记。这种方法可以在检测器性能下降很小的情况下显著减少数据标记量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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