Classification of doll image dataset based on human experts and computational methods: A comparative analysis

Masataka Morishita, Miki Ueno, H. Isahara
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引用次数: 1

Abstract

In this paper, we analyze the important features for the difficult dataset to classify, comparing the process between human experts and computational method in order to built useful application on specific domain utilizing only computational techniques at practical level. To achieve this, “Doll” images dataset were constructed and the features were described in detail. After that, two types of experiments were carried out between human beginner participants and computational method. As a results, we obtained typical features of this dataset and discussed for applying the method to similar domains. In addition, the results suggest that it is efficient for classifying such a dataset to combine human experts knowledge and computational way.
基于人类专家和计算方法的娃娃图像数据集分类:比较分析
本文分析了难以分类的数据集的重要特征,比较了人工专家和计算方法的分类过程,以期在实际层面上仅利用计算技术在特定领域构建有用的应用程序。为此,构建了“Doll”图像数据集,并对其特征进行了详细描述。之后,在人类初学者和计算方法之间进行了两类实验。结果,我们获得了该数据集的典型特征,并讨论了将该方法应用于类似领域的方法。此外,结果表明,将人类专家知识与计算方法相结合,对此类数据集进行分类是有效的。
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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