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相关概念视频

Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...

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用机器学习驱动的随机建模方法从二维图像进行3D青混合重建

Jiayu Zhang1, Liang Huang1

  • 1School of Civil Engineering, Zhengzhou University, Zhengzhou 450001, China.

Materials (Basel, Switzerland)
|August 28, 2025
PubMed
概括

我们使用图像分析和随机建模开发了一种低成本的3D青混合重建方法. 这种方法准确地捕捉空间结构和材料特性,以便更好地理解青的行为.

科学领域:

  • 材料科学
  • 土木工程
  • 计算模型

背景情况:

  • 准确的3D模型对于理解青混合物的行为以及空间结构与物理特性之间的关系至关重要.
  • 现有的3D重建方法可能昂贵且数据密集.

研究的目的:

  • 开发一个低成本和数据效率的框架来创建3D青混合物模型.
  • 整合基础细分和随机建模以进行增强的重建.

主要方法:

  • 使用智能手机摄影和图像布进行二维图像捕捉.
  • 采用细分任何模型 (SAM) 进行高质量的聚合物和青粘合剂细分.
  • 应用多点统计 (MPS) 与近邻模拟 (NNSIM) 进行高效的3D模型构建.
  • 引入了一个概率聚合框架来计算3D条件概率.

主要成果:

  • 从二维图像成功重建了三维青混合物模型.
  • 使用两点相关函数,距离分析和粒度分布验证重建质量.
  • 在材料生产中证明了空间模式的保存和不确定性的表现.

结论:

  • 拟议的方法为3D青混合物重建提供了成本效益高效的方法.
关键词:
三维模型青混合物多点统计任何部分的模型

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  • 该框架准确地代表了青材料的复杂空间结构和特性.
  • 这种技术有助于了解青的行为和优化材料生产.