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

Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

188
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
188
Classification of Systems-II01:31

Classification of Systems-II

134
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
134
Classification of Systems-I01:26

Classification of Systems-I

169
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
169
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

38
Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
38
Aggregates Classification01:29

Aggregates Classification

303
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
303
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

3.3K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
3.3K

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

Hand Gesture Recognition in Automotive Human⁻Machine Interaction Using Depth Cameras.

Sensors (Basel, Switzerland)·2018
查看所有相关文章

相关实验视频

Updated: Jun 5, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K

在评估图像分类模型选择分数时,一个尺寸不适合所有人.

Nermeen Abou Baker1, Uwe Handmann2

  • 1Computer Science Department, Ruhr West University of Applied Sciences, Bottrop, Germany. nermeen.baker@hs-ruhrwest.de.

Scientific reports
|December 5, 2024
PubMed
概括

本研究评估了14个可转移性得分,用于选择预训练的图像分类模型,从而降低计算成本. 调查结果显示,得分的有效性因数据集和模型类型而异,视觉转换器 (ViT) 经常表现出色.

科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 人工智能的人工智能

背景情况:

  • 选择预训练模型用于图像分类通常需要广泛的微调.
  • 缺乏对可转移性得分的标准化评估,这阻碍了有效的模型选择.
  • 减少模型选择中的计算负担对于实际应用至关重要.

研究的目的:

  • 评估14个可转移性得分的有效性,以对预训练模型进行排名.
  • 提供一个一致的方法,在模型选择中平衡准确性和效率.
  • 为了指导从业者在选择最佳模型时,不需要详尽的微调.

主要方法:

  • 在11个基准数据集中评估了14个可转移性得分.
  • 包括卷积神经网络 (CNN) 和视觉转换器 (ViT) 模型.
  • 确保一致的实验条件,以减轻先前研究的变化.

主要成果:

  • 根据数据集特征和模型架构,可转移性评分的有效性差异很大.
  • 视觉变压器 (ViT) 模型显示出卓越的可转移性,特别是在细粒度数据集上.
  • 没有一个单一的得分被证明是普遍最佳的;有效性取决于背景.
关键词:
图像的分类图像的分类.模型排名 模型排名模型选择 模型选择转移学习转移学习估计可转移性估计

更多相关视频

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.3K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K

相关实验视频

Last Updated: Jun 5, 2025

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

7.4K
Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
08:20

Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images

Published on: October 27, 2023

1.3K
Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

10.6K

结论:

  • 该研究提供了对选择适当的可转移性得分来进行优化模型选择的见解.
  • 通过考虑计算效率,确定了适合资源有限环境的得分.
  • 旨在促进在实践中更有效地部署图像分类模型.