Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

13.9K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
13.9K
Vector Representation of Complex Numbers01:16

Vector Representation of Complex Numbers

129
Complex numbers, represented in Cartesian coordinates, can also be visualized as vectors. These vectors can be expressed in polar form, emphasizing their magnitude and angle. When a complex number is input into a function, the output is another complex number, highlighting the function's zero point from which the vector representation can originate.
Consider a function defined as the product of the complex factors in the numerator divided by the product of the complex factors in the...
129
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

12.2K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
12.2K
Vector Operations01:20

Vector Operations

1.3K
Vectors are physical quantities that have both magnitude and direction. The vector operations include addition, subtraction, and scalar multiplication.
A vector multiplied by a scalar value is called scalar multiplication. The result obtained is a new vector with a different magnitude. If the scalar is positive, the direction of the vector remains the same, but if it is negative, the direction of the vector is reversed. For example, the product of the mass and velocity yields the momentum.
1.3K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

S-to-O Atom Swapping Unlocks a Promising Difuranphthalimide-Based Polymer Donor with Efficiency over 20.

Journal of the American Chemical Society·2026
Same author

Systematic Identification of Immune Regulatory Gene Networks in Leukemia Using Integrated Transcriptomic and Functional Analyses.

Current pharmaceutical biotechnology·2026
Same author

Ultrasound-Assisted Curdlan Curing Reduces Water Loss of Rabbit Meat: Water Retention Performance, Myofibrillar Protein Structure, and Processing Adaptability.

Foods (Basel, Switzerland)·2026
Same author

Predictive value of miR-132-3p for the onset of sepsis-induced acute kidney injury and its functional role during disease development.

Personalized medicine·2026
Same author

Longitudinal Interplay Between Cognitive Impairment and Frailty: A Dual Trajectory Analysis Among Chinese Older Adults.

Geriatrics & gerontology international·2026
Same author

Mitophagy-Oxidative Stress Molecular Subtypes Define an Immunosuppressive Ecosystem and Vulnerabilities in Glioblastoma.

Journal of cellular and molecular medicine·2026

相关实验视频

Updated: Jul 11, 2025

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro
08:00

Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro

Published on: December 3, 2018

8.4K

VQ-NeRF:神经反射分解和编辑与矢量量子化.

Hongliang Zhong, Jingbo Zhang, Jing Liao

    IEEE transactions on visualization and computer graphics
    |November 13, 2023
    PubMed
    概括

    我们介绍VQ-NeRF,这是一个用于3D场景的新型神经网络. 该模型通过量化连续反射场,减少噪声和简化交互,使离散材料的编辑成为可能.

    科学领域:

    • 计算机视觉 计算机视觉
    • 计算机图形 计算机图形
    • 机器学习 机器学习

    背景情况:

    • 传统的神经反射场利用3D场景的连续表示.
    • 这种连续的方法可以在现实中导致杂的材料分解和复杂的编辑过程.
    • 现实世界的物体通常由离散材料组成.

    研究的目的:

    • 开发一种用于在3D场景中编辑离散材料的新方法.
    • 解决神经反射场中连续表示的局限性.
    • 为了在3D环境中实现对材料的直观和精确操纵.

    主要方法:

    • 提出VQ-NeRF,这是一个采用矢量量化 (VQ) 的双分支神经网络.
    • 一个连续分支预测了分解材料,而一个离散分支则使用VQ.将这些材料量化为单个材料.
    • 采用基于丢失的VQ代码词排名策略来确定材料数量并减少细分冗余.

    主要成果:

    • VQ-NeRF成功地将连续反射场分解和量化为离散材料.
    • 该模型生成一个细分图,方便编辑特定材料的轻松选择.
    • 在合成和现实世界的场景中,在材料分解和编辑方面取得了卓越的性能.

    更多相关视频

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
    07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.4K
    High-speed Particle Image Velocimetry Near Surfaces
    11:59

    High-speed Particle Image Velocimetry Near Surfaces

    Published on: June 24, 2013

    33.1K

    相关实验视频

    Last Updated: Jul 11, 2025

    Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro
    08:00

    Meso-Scale Particle Image Velocimetry Studies of Neurovascular Flows In Vitro

    Published on: December 3, 2018

    8.4K
    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
    07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.4K
    High-speed Particle Image Velocimetry Near Surfaces
    11:59

    High-speed Particle Image Velocimetry Near Surfaces

    Published on: June 24, 2013

    33.1K

    结论:

    • VQ-NeRF是第一个能够在3D场景中进行离散材料编辑的模型.
    • 拟议的VQ机制大大降低了噪音,并提高了材料编辑的可用性.
    • 双分支架构有效地弥合了连续表示和离散的现实世界材料之间的差距.