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TRAINING SET SUFFICIENCY FOR IMAGE ANALYSIS

机译:培训集合图像分析

摘要

Aspects of the technology described herein improve an object recognition system by specifying a type of picture that would improve the accuracy of the object recognition system if used to retrain the object recognition system. The technology described herein can take the form of an improvement model that improves an object recognition model by suggesting the types of training images that would improve the object recognition model's performance. For example, the improvement model could suggest that a picture of a person smiling be used to retrain the object recognition system. Once trained, the improvement model can be used to estimate a performance score for an image recognition model given the set characteristics of a set of training of images. The improvement model can then select a feature of an image, which if added to the training set, would cause a meaningful increase in the recognition system's performance.
机译:本文描述的技术的各方面通过指定用于重置对象识别系统的图像可以提高物体识别系统的准确性来改进对象识别系统。这里描述的技术可以采用改进模型的形式,该改进模型通过建议提高对象识别模型的性能的训练图像的类型来改善对象识别模型。例如,改进模型可能表明,微笑的人的图片用于重新训练对象识别系统。一旦训练,改善模型可用于估计给定图像识别模型的性能分数给定考虑到一组图像训练的特征。然后,改进模型可以选择图像的特征,如果添加到训练集,则会导致识别系统的性能有意义。

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