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

Vertical Curve: Problem Solving01:23

Vertical Curve: Problem Solving

677
Vertical curves provide the transition between two roadway grades, ensuring safety, comfort, and functionality. Calculating elevations at specific stations along the curve involves several systematic steps based on the curve's geometry and provided design parameters.The vertical curve is defined by its length, grades, Point of Vertical Intersection (P.V.I.) location, and P.V.I. elevation. The stations of the Point of Vertical Curvature (P.V.C.), where the curve begins, and the Point of Vertical...
677
Application of Linearization and Approximation01:29

Application of Linearization and Approximation

193
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
193
Transformations of Functions I01:29

Transformations of Functions I

286
A function's graph can be modified by changing its position or size without altering its overall shape. These transformations allow the graph to be moved across the coordinate plane while preserving its pattern and structure. One of the most common transformations is shifting, which repositions the graph without distorting it.When the output of a function is adjusted by adding or subtracting a constant, the graph shifts vertically. A positive value moves the graph upward, while a negative value...
286
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

451
The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all...
451
Transformations of Functions III01:20

Transformations of Functions III

304
Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
304
Types of Limits II01:24

Types of Limits II

268
When observing how a curve behaves near a specific point along the horizontal axis, there are cases where the curve’s height increases or decreases without limit as the position draws closer to that point. The curve does not settle at any particular value; instead, the values grow more extreme—upward or downward—the nearer they get. No defined value exists exactly at that location, yet the surrounding behavior becomes more dramatic, indicating a sharp change in direction.The...
268

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

Graph Neural Network-Based Node Deployment for Throughput Enhancement.

IEEE transactions on neural networks and learning systems·2023
Same author

Enhanced electrochemical detection of erythromycin based on acetylene black nanoparticles.

Colloids and surfaces. B, Biointerfaces·2010
Same author

Enhancement of catalytic performance in asymmetric transfer hydrogenation by microenvironment engineering of the nanocage.

Chemical communications (Cambridge, England)·2010
Same author

Pharmacology of a potent and selective inhibitor of PDE4 for inhaled administration.

European journal of pharmacology·2010
Same author

Gypenosides protects dopaminergic neurons in primary culture against MPP(+)-induced oxidative injury.

Brain research bulletin·2010
Same author

[Pathogen identification of Pinellia ternata tuber disease and selection of fungicide].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica·2010

相关实验视频

Updated: May 3, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K

GRAM:使用梯度注意力图进行图形异常检测的可解释方法.

Yifei Yang1, Peng Wang2, Xiaofan He3

  • 1Electronic Information School, Wuhan University, Hubei, China; Data Science Research Center, Duke Kunshan University, Jiangsu, China.

Neural networks : the official journal of the International Neural Network Society
|June 22, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种可解释的图形异常检测方法,使用图形神经网络的注意力图. 这种新的方法提高了检测性能,并为决策过程提供了洞察力.

关键词:
异常检测检测异常检测图形神经网络是一个神经网络.可以解释性 解释性

更多相关视频

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

517
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K

相关实验视频

Last Updated: May 3, 2026

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

14.7K
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

517
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

2.7K

科学领域:

  • 数据挖掘 数据挖掘
  • 机器学习 机器学习
  • 网络分析 网络分析

背景情况:

  • 图形数据分析对于识别不寻常模式至关重要.
  • 目前的异常检测方法缺乏一致的性能和可解释性.
  • 了解异常检测决策至关重要,但往往很困难.

研究的目的:

  • 提出一种新的,可解释的图形异常检测方法.
  • 通过可解释性来提高异常检测性能.
  • 提供有关异常检测决策过程的见解.

主要方法:

  • 从图表神经网络梯度中提取注意力图.
  • 使用注意力地图进行异常得分.
  • 在各种异常检测设置中应用该方法.

主要成果:

  • 理论分析使用合成数据验证了该方法.
  • 对现实世界数据集的广泛评估显示出卓越的性能.
  • 拟议的方法优于最先进的图形异常检测技术.

结论:

  • 新的可解释方法显著改善了图形异常检测.
  • 来自GNN梯度的注意力图提供了有效的异常得分.
  • 该方法在各种数据集上展示了灵活性和卓越的性能.