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相关概念视频

Bias01:22

Bias

4.3K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
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相关实验视频

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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

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使用机器学习图像分析探索艺术中的主题和偏见.

Sudeepti Surapaneni1, Sana Syed1, Logan Yoonhyuk Lee1

  • 1School of Data Science University of Virginia Charlottesville, USA.

Proceedings of the ... IEEE Systems and Information Engineering Design Symposium. IEEE Systems and Information Engineering Design Symposium
|July 10, 2023
PubMed
概括

这项研究将深度学习应用到来自Met的自动化艺术图像分类.

科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 艺术史 艺术史 艺术史

背景情况:

  • 博物馆越来越多地提供开放式收藏.
  • 手工对艺术品进行注释是费力和耗时的.
  • 用精确标记的艺术品增强用户体验对于开放式收藏至关重要.

研究的目的:

  • 应用机器学习来自动分类来自大都会公开访问收藏的艺术图像.
  • 为了比较ResNet 50,ResNet 101和Inception-ResNet-V2模型的性能.
  • 使用梯度加权类激活地图 (Grad-CAMs) 增强模型的解释性,并探索性别标签中的潜在偏见.

主要方法:

  • 卷积神经网络 (CNN):ResNet 50,ResNet 101,Inception-ResNet-V2. 这些神经网络可以通过
  • 梯度加权的类激活地图 (Grad-CAMs) 用于模型的解释性.
  • 使用ResNet 50实现多标签分类.

主要成果:

  • 对艺术图像分类的三种深度学习模型进行比较分析.
  • 通过可解释的人工智能技术识别性别标签中的潜在偏见.
  • 成功实施多标签分类模型.
关键词:
美国有线电视新闻网 (CNN)深度学习是一种深度学习.图像的分类图像的分类.

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结论:

  • 深度学习为大型艺术收藏提供了对手动注释的可行替代方案.
  • 像Grad-CAMs这样的可解释AI方法对于理解模型行为和偏见至关重要.
  • 自动化艺术图像分类可以显著提高用户对开放博物馆藏品的参与度.