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Deep active learning method for civil infrastructure defect detection

机译:用于民用基础设施缺陷检测的深度主动学习方法

摘要

An image processing system includes a memory to store a classifier and a set of labeled images for training the classifier, wherein each labeled image is labeled as either a positive image that includes an object of a specific type or a negative image that does not include the object of the specific type, wherein the set of labeled images has a first ratio of the positive images to the negative images. The system includes an input interface to receive a set of input images, a processor to determine a second ratio of the positive images, to classify the input images into positive and negative images to produce a set of classified images, and to select a subset of the classified images having the second ratio of the positive images to the negative images, and an output interface to render the subset of the input images for labeling.
机译:图像处理系统包括用于存储分类器的存储器和用于训练分类器的一组标记图像,其中每个标记图像被标记为包括特定类型的对象的正图像或不包括特定类型对象的负图像。特定类型的物体,其中该组标记图像具有正图像与负图像的第一比率。该系统包括:输入接口,用于接收一组输入图像;处理器,用于确定正图像的第二比例;将输入图像分类为正图像和负图像,以产生一组分类图像;以及选择图像的子集。具有正图像与负图像的第二比率的分类图像,以及用于渲染输入图像的子集以进行标记的输出接口。

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