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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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一个混合深度增强框架,具有适应性标签稳定,用于基于SEM的浮孔度估计,用于飞灰水泥砂

Abdullah1,2, Muhammad Ateeb Ather1,2, José Luis Oropeza Rodríguez1

  • 1Center for Computing Research, Instituto Politécnico Nacional, Mexico City, Mexico.

Frontiers in artificial intelligence
|March 11, 2026
PubMed
概括

本研究引入了一种新的混合深度增强框架,用于从SEM图像中准确地估计水泥孔度. 该方法通过融合深度学习和传统特征来提高可靠性,克服先前技术的局限性.

关键词:
在 SEM 图像分析中,图像分析是最重要的.混凝土材料是一种固体材料.功能互动注意力注意力渐变增强组合组合的渐变.混合深度学习是混合深度学习.材料信息学 材料信息学孔隙性估计的估计.自主监督学习学习

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