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相关概念视频

Transformers01:26

Transformers

1.1K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
1.1K
Types Of Transformers01:16

Types Of Transformers

972
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
972
The Ideal Transformer01:26

The Ideal Transformer

387
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
387
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

151
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
151
Transformers in Distribution System01:27

Transformers in Distribution System

102
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
102
Energy Losses in Transformers01:21

Energy Losses in Transformers

867
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
867

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相关实验视频

Updated: Jun 29, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
04:23

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

Published on: April 21, 2023

1.8K

增强风格的变压器用于建筑场景中的图像标题.

Kani Song1, Linlin Chen1, Hengyou Wang1

  • 1School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China.

Entropy (Basel, Switzerland)
|March 28, 2024
PubMed
概括
此摘要是机器生成的。

一个新的风格增强的图像标题转换器 (SETCAP) 改善了建筑工地监控. 这种模型增强了图像的理解,并为复杂的场景生成了更准确的描述.

关键词:
建筑现场的建筑现场.图片标题图片标题图片标题风格 风格特征 风格特征 风格特征变压器变压器变压器变压器

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Last Updated: Jun 29, 2025

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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images

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科学领域:

  • 计算机视觉 计算机视觉
  • 人工智能的人工智能
  • 建设管理建设管理.

背景情况:

  • 图像标题对于建筑项目情报和现场活动监测至关重要.
  • 现有的图像标题模型与建筑场景的复杂性作斗争.
  • 缺乏专门的数据集和建筑图像模型阻碍了进步.

研究的目的:

  • 开发一个针对复杂建筑环境而定制的高级图像标题模型.
  • 提高建筑工地活动生成的标题的准确性和相关性.
  • 增强建筑项目管理中的智能和自动化能力.

主要方法:

  • 为图像标题 (SETCAP) 提出了一种新型风格增强的变压器.
  • 斯温变压器用于网格特征提取,通过样式编码器将样式信息纳入.
  • 风格信息被整合到解码器中的文本特征中,用于逐字生成句子.
  • 添加了一个句子风格丢失,以使生成的标题与训练数据风格保持一致.

主要成果:

  • 拟议的SETCAP模型在MSCOCO和MOCS数据集上取得了显著的改进.
  • SETCAP的表现超过了最先进的方法,在MOCS上显示了4.2%的CIDEr得分增加.
  • 在MSCOCO数据集上观察到3.9%的CIDEr得分改善,证明了广泛的适用性.

结论:

  • 在复杂的建筑场景中,SETCAP模型有效地解决了现有方法的局限性.
  • 整合风格信息可以提高专门领域的图像标题的性能.
  • 开发的模型为智能施工管理和现场活动分析提供了一个有前途的解决方案.