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相关概念视频

Gauss's Law: Cylindrical Symmetry01:20

Gauss's Law: Cylindrical Symmetry

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A charge distribution has cylindrical symmetry if the charge density depends only upon the distance from the axis of the cylinder and does not vary along the axis or with the direction about the axis. In other words, if a system varies if it is rotated around the axis or shifted along the axis, it does not have cylindrical symmetry. In real systems, we do not have infinite cylinders; however, if the cylindrical object is considerably longer than the radius from it that we are interested in,...
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Polar and Cylindrical Coordinates01:22

Polar and Cylindrical Coordinates

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The Cartesian coordinate system is a very convenient tool to use when describing the displacements and velocities of objects and the forces acting on them. However, it becomes cumbersome when we need to describe the rotation of objects. So, when describing rotation, the polar coordinate system is generally used.
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Spherical Coordinates01:23

Spherical Coordinates

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Spherical coordinate systems are preferred over Cartesian, polar, or cylindrical coordinates for systems with spherical symmetry. For example, to describe the surface of a sphere, Cartesian coordinates require all three coordinates. On the other hand, the spherical coordinate system requires only one parameter: the sphere's radius. As a result, the complicated mathematical calculations become simple. Spherical coordinates are used in science and engineering applications like electric and...
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Gauss's Law: Spherical Symmetry01:26

Gauss's Law: Spherical Symmetry

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A charge distribution has spherical symmetry if the density of charge depends only on the distance from a point in space and not on the direction. In other words, if the system is rotated, it doesn't look different. For instance, if a sphere of radius R is uniformly charged with charge density ρ0, then the distribution has spherical symmetry. On the other hand, if a sphere of radius R is charged so that the top half of the sphere has a uniform charge density ρ1 and the bottom half...
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Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

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In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position...
347
Centroid for the Paraboloid of Revolution01:16

Centroid for the Paraboloid of Revolution

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The paraboloid of revolution is an axially symmetric surface generated by rotating a parabola around its axis. This shape has several applications in mechanical engineering due to its advantageous structural properties, such as strength against stress concentration points and rotational symmetry.
The centroid for the paraboloid of revolution is the point where all the mass of the paraboloid is concentrated. This centroid is important for engineering applications, as it determines how forces are...
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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学习内容加权的伪圆柱体表示用于360度图像压缩.

Mu Li, Youneng Bao, Xiaohang Sui

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    概括
    此摘要是机器生成的。

    本研究介绍了360度图像压缩的内容适应方法,解决了在等直角投影 (ERP) 中的非均采样问题. 这种新的方法优化了基于图像内容和采样率的压缩,以提高视觉质量.

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    相关实验视频

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    科学领域:

    • 计算机视觉 计算机视觉
    • 图像处理 图像处理
    • 机器学习 机器学习

    背景情况:

    • 使用等直角投影 (ERP) 进行学习的360°图像压缩,由于采样不均而面临挑战.
    • 现有的方法经常使用统一的抽样,忽视图像内容的意义.

    研究的目的:

    • 为360度图像压缩开发一个内容适应性参数表示.
    • 通过考虑内容和采样率来提高压缩效率和视觉质量.

    主要方法:

    • 引入了一个参数伪圆柱形表示和卷积操作.
    • 模拟的表示超参数使用基于图像内容和球形坐标的网络输出.
    • 采用超学习算法来优化编解码器和超参数估计网络.
    • 开发了一种用于速率扭曲损失的新型放松方法,以实现基于梯度的优化.

    主要成果:

    • 在全向图像压缩上实现了最先进的性能.
    • 与现有方法相比,显示出优越的视觉质量.
    • 通过meta-learning成功优化了针对不同压缩任务的超参数.

    结论:

    • 内容适应性参数表示对于有效的360°图像压缩至关重要.
    • 提出的超学习方法与放松的损失优化增强了压缩性能.
    • 该方法在已知的360度图像压缩技术中提供了重大进步.