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相关概念视频

Non-equilibrium in the Cell01:16

Non-equilibrium in the Cell

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An important concept in studying metabolism and energy is that of chemical equilibrium. Most chemical reactions are reversible. They can proceed in both directions, releasing energy into their environment in one direction, and absorbing it from the environment in the other direction. The same is true for the chemical reactions involved in cell metabolism, such as the breaking down and building up of proteins into and from individual amino acids, respectively. Reactants within a closed system...
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相关实验视频

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强大的假新闻检测组合技术:整合变压器,自然语言处理和机器学习.

Mohammed Al-Alshaqi1, Danda B Rawat1, Chunmei Liu1

  • 1Department of Electrical Engineering and Computer Science, Howard University, Washington, DC 20059, USA.

Sensors (Basel, Switzerland)
|September 28, 2024
PubMed
概括

这项研究引入了一个强大的框架,用于检测文本,图像和视频中的假新闻. 多式联运方法显著提高了准确性,提供了对抗在线错误信息的强大工具.

科学领域:

  • 人工智能的人工智能
  • 计算机科学 计算机科学
  • 信息科学 信息科学 信息科学

背景情况:

  • 通过文本,图像和视频传播虚假新闻是一个重大挑战.
  • 先进的检测方法对于导航现代信息格局至关重要.
  • 现有的方法往往专注于单一的模式,限制了全面的假新闻识别.

研究的目的:

  • 提出一个全面的框架,用于虚假新闻检测,整合文本,图像和视频.
  • 开发和评估机器学习和深度学习模型,用于多式联网假新闻分析.
  • 为了解决现代信息传播和操纵的复杂性.

主要方法:

  • 采用了双阶段的方法,首先是使用各种分类器进行文本数据分析.
  • 开发了一种多模式方法,将文本的变压器双向编码器表示 (BERT) 和视觉数据的卷积神经网络 (CNN) 结合起来.
  • 在ISOT假新闻数据集和MediaEval 2016图像验证库上进行了实验.

主要成果:

  • 随机森林分类器在文字数据分析中实现了99%的准确性.
  • 多式联运方法在基线模型中表现出优越的性能.
  • 与现有的多式联运技术相比,拟议的多式联运框架显示了3.1%的精度改进.
关键词:
贝尔特 (BERT) 公司在美国,CNN是CNN.在NLP中,我们使用了NLP.假新闻检测 假新闻检测机器学习是机器学习.多模式数据多模式数据变压器 变压器 变压器

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结论:

  • 开发的框架为在各种媒体格式中检测假新闻提供了强大的和可适应的解决方案.
  • 该研究强调了整合文本和视觉分析的有效性,以改善假新闻检测.
  • 这项研究通过提供分析复杂信息生态系统的先进工具,有助于打击错误信息.