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相关概念视频

Labeling Emotion01:20

Labeling Emotion

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Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...
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相关实验视频

Updated: Jan 12, 2026

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application
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通过标签语义驱动的特征交互增强的多标签舌头图像分类.

Xiang Lu1, Yue Feng1, Xudong Jia2

  • 1School of Electronics and Information Engineering Wuyi University, Jiangmen 529020, China.

Computational biology and chemistry
|November 8, 2025
PubMed
概括

这项研究引入了在传统中医 (TCM) 中对舌头图像进行分类的新框架,通过更好地利用标签语义和智能医疗应用的功能交互来提高诊断准确性.

关键词:
内容引导的注意力 内容引导的注意力交叉模式特征融合 交叉模式特征融合在实例级别的代表.标签-语义驱动的驱动多标签的舌头图像分类

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Last Updated: Jan 12, 2026

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科学领域:

  • 医学成像分析 医学成像分析
  • 医疗保健中的人工智能
  • 传统中国医学 诊断 诊断 诊断

背景情况:

  • 舌头图像的多标签分类对于传统中医 (TCM) 中的智能诊断至关重要.
  • 现有的方法与标签语义,本地特征和层次特征集成扎,限制了分类性能.
  • 需要改进的方法来弥合语义差距,并利用全面的特征表示来进行准确的医学诊断.

研究的目的:

  • 提出一个新的多标签的舌头图像分类框架,标签语义驱动的特征交互增强 (LSDFIE).
  • 通过将标签语义与本地和空间特征集成来提高跨模式交互效率.
  • 通过有效利用等级特征之间的协同和互补机制来提高分类性能.

主要方法:

  • LSDFIE框架集成了实例级 (本地) 和空间级 (上下文) 的表示.
  • 交叉模式融合模块将标签语义与本地语言图像特征对齐,使用低级别的双线注意力.
  • 一个图像模式注意力增强模块评估空间级和实例级表示之间的相关性,由内容注意力引导的融合.

主要成果:

  • 拟议的方法在MlLTID数据集上实现了93.02%的平均平均精度 (mAP),在牙标记数据集上达到95.33%.
  • 在胸部X射线14数据集上,LSDFIE在曲线下的面积 (AUC) 为84.11%,超过了最先进的0.36%.
  • 在各种医学成像任务中表现出卓越的分类准确性和强大的概括能力.

结论:

  • LSDFIE框架有效地弥合了模式之间的语义差距,并全面利用层次特征.
  • 该方法显著增强了歧视性特征,同时抑制了不相关的特征,从而实现了强大的识别.
  • 经过验证的卓越性能突显了LSDFIE在推进TCM和更广泛的医疗保健应用中的智能诊断方面的潜力.