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Webpage segmentation for extracting images and their surrounding contextual information

机译:用于提取图像的网页分段及其周围的上下文信息

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Web images come in hand with valuable contextual information. Although this information has long been mined for various uses such as image annotation, clustering of images, inference of image semantic content, etc., insufficient attention has been given to address issues in mining this contextual information. In this paper, we propose a webpage segmentation algorithm targeting the extraction of web images and their contextual information based on their characteristics as they appear on webpages. We conducted a user study to obtain a human-labeled dataset to validate the effectiveness of our method and experiments demonstrated that our method can achieve better results compared to an existing segmentation algorithm.
机译:网络图像与宝贵的上下文信息一起出现。虽然该信息长期以来用于各种用途,例如图像注释,图像的聚类,图像语义内容的群集,也不足够的注意力来解决挖掘这种上下文信息的问题。在本文中,我们提出了一种基于它们在网页上显示的特征来提取网页分割算法及其基于它们的特征来提取Web图像及其上下文信息。我们进行了一个用户学习,以获得人类标记的数据集以验证我们的方法和实验的有效性,证明我们的方法可以实现与现有分割算法相比的更好的结果。

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