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Updated: Jun 27, 2025

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Deep Neural Networks for Image-Based Dietary Assessment
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数据集用于多式联运假新闻检测和验证任务
Alessandro Bondielli1, Pietro Dell'Oglio2, Alessandro Lenci3
1Department of Computer Science, University of Pisa, Largo Bruno Pontecorvo, 3, 56127, Pisa, Italy.
Data in brief
|May 7, 2024
概括
这项研究引入了一套新的意大利数据集,用于多式联运假新闻检测,这对于打击在线虚假信息至关重要. 它有助于开发分析文本和图像的系统,以有效地识别假新闻.
科学领域:
- 自然语言处理自然语言处理.
- 计算机视觉 计算机视觉
- 信息科学 信息科学 信息科学
背景情况:
- 在线虚假信息和假新闻是一个重大挑战,特别是在突发新闻事件期间.
- 虽然文本是主要的媒介,但多式联络内容 (文本,图像) 越来越多地用于传播错误信息.
- 现有的多式联运数据集很少,特别是对于像意大利语这样的低资源语言.
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