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Updated: Jan 9, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
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基于物理的机器学习,用于从IR图像中预测导热性

Shinto Mundackal Francis1, Andrew Ferebee1, Sajib Kumar Mohonta1

  • 1Laboratory of Nano-Biophysics, Department of Physics and Astronomy, Clemson University, Clemson, South Carolina 29634, United States.

ACS applied materials & interfaces
|December 4, 2025
PubMed
概括

本研究介绍了一种机器学习框架,使用红外热学来快速预测聚合物复合材料热接口材料 (PC-TIM) 的热导率. 这种方法为材料开发和质量控制提供了可扩展的诊断.

关键词:
科姆索尔 (COMMSOL) 是一个国家.在SHAP分析中,我们分析了SHAP.石墨烯是一种石墨烯.红外热像学 红外热像学 红外热像学机器学习是机器学习.聚合物复合物的聚合物复合物.导热率 导热率 导热率 导热率 导热率 导热率

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