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相关概念视频

Introduction to the Sign Test01:10

Introduction to the Sign Test

1.3K
The sign test is an important tool in nonparametric statistics, offering a straightforward yet effective method for analyzing matched pairs, nominal data, or hypotheses concerning the median of a population. It transforms data points into positive or negative signs, avoiding the need for assumptions about data distribution and instead focusing on the direction of change. It is particularly valuable when data does not conform to the normal distribution requirements of many parametric tests. For...
1.3K
Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

486
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
486
Sign Test for Nominal Data01:12

Sign Test for Nominal Data

460
The sign test is a nonparametric method used to evaluate hypotheses about the median of a single sample or to compare the medians of two related samples. The sign test is particularly useful when dealing with nominal data, which includes distinct categories without an inherent order, such as names, labels, and preferences. Nominal data restricts statistical analysis to evaluating population proportions rather than mean or median values that require continuous data.
For example, consider a...
460
Sign Test for Median of Single Population01:20

Sign Test for Median of Single Population

445
In general, the sign test serves as a nonparametric method to test hypotheses about the median of a single population when the data does not follow a known distribution. This simplicity makes it particularly useful for small sample sizes or when the assumptions of parametric tests cannot be met. The process begins with identifying a null hypothesis, typically stating that the population median equals a specific value. The alternative hypothesis could be that the median is either not equal to,...
445
Sign Convention01:30

Sign Convention

3.8K
When analyzing a beam subjected to various loads, it is crucial to understand the internal forces and moments generated within the structure. These internal forces can be broadly classified into normal forces, shear forces, and bending moments. To determine these forces and moments, we use the method of sections and apply a specific sign convention based on their direction and the side of the section being analyzed.
The normal force acts perpendicular to the beam's cross-section and can...
3.8K
Larynx01:21

Larynx

6.4K
The human larynx, often referred to as the voice box, is an intricate organ located in the neck. It serves as a pathway for air to enter the lungs during respiration and is an essential component of voice production.
Anatomy of the Larynx
The larynx consists of various components, including cartilage, muscles, and vocal cords. Its structure includes three large unpaired cartilages—the thyroid, cricoid, and epiglottis—and three smaller paired cartilages—the arytenoids,...
6.4K

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相关实验视频

Updated: May 5, 2026

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
05:58

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

4.5K

LSWH100:使用SignWriting的巴西手语 (Libras) 的手形数据集.

Vicente Coelho Lobo-Neto1, Helio Pedrini1

  • 1Institute of Computing, University of Campinas, Av. Albert Einstein 1251, Campinas, SP 13083-852, Brazil.

Data in brief
|August 30, 2024
PubMed
概括

一个名为Libras SignWriting Handshape (LSWH100) 的新数据集提供了144,000个合成图像,用于识别巴西手语 (Libras). 这个资源有助于推动手语技术的发展.

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 语言学的语言学.

背景情况:

  • 标语识别对于通讯可访问性至关重要.
  • 现有的数据集可能缺乏手形和现实世界条件的多样性.
  • 巴西手语 (Libras) 需要专门的资源来准确识别.

研究的目的:

  • 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集. 介绍Libras SignWriting Handshape (LSWH100) 数据集.
  • 为培训和评估手语识别模型提供全面的资源.
  • 促进手形分类,检测,细分和3D姿势估计的研究.

主要方法:

  • 使用Blender生成了144,000个合成图像.
  • 包括来自巴西手语 (Libras) 的 100 个不同的手形类.
  • 有注释的图像与分类,检测,细分,深度和3D关键点.
关键词:
计算机视觉 计算机视觉 计算机视觉手的配置识别手的配置识别.手指关键点的关键点手形识别手形识别功能

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Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment
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Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment

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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

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相关实验视频

Last Updated: May 5, 2026

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
05:58

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

4.5K
Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment
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Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment

Published on: December 23, 2020

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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

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主要成果:

  • 创建了一个多样化的数据集,尺寸,旋转,皮肤色调和场景条件的变化.
  • 该数据集具有使用SignWriting规范命名的手形.
  • LSWH100为手语识别任务提供了一个具有挑战性的基准.

结论:

  • LSWH100数据集是促进天秤座识别的宝贵资源.
  • 这一数据集有可能显著提高手语识别系统的性能.
  • LSWH100的可用性可以对聋人社区的沟通产生积极影响.