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相关概念视频

Types Of Transformers01:16

Types Of Transformers

1.1K
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...
1.1K
Transformers in Distribution System01:27

Transformers in Distribution System

165
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...
165
The Ideal Transformer01:26

The Ideal Transformer

915
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...
915
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

213
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...
213
Transformers01:26

Transformers

1.2K
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...
1.2K
Energy Losses in Transformers01:21

Energy Losses in Transformers

985
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...
985

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相关实验视频

Updated: Sep 17, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
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Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

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CTFS:一个整合的变压器框架,例如和语义细分任务.

Kun Dai1, Fuyuan Qiu2, Hongbo Gao2

  • 1State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150006, China; Yangtze River Delta HIT Robot Technology Research Institute, Wuhu, 241000, China.

Neural networks : the official journal of the International Neural Network Society
|June 27, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了用于同时实例和语义细分的整合变压器框架 (CTFS). CTFS采用新的策略来优化共享参数和解决梯度冲突,提高计算机视觉模型的性能.

关键词:
渐变冲突的冲突.实例细分是指实例的细分.多任务学习是多任务学习.语义细分 语义细分是指语义细分.

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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
  • 深度学习 (Deep Learning) 是一种深度学习.
  • 机器学习 机器学习

背景情况:

  • 实例和语义细分是计算机视觉的关键任务.
  • 现有的统一变压器框架与并发的多任务优化和梯度冲突作斗争.

研究的目的:

  • 开发一个合并的变压器框架 (CTFS) 以实现高效的同时实例和语义细分.
  • 解决多任务学习中优化共享参数和减轻梯度冲突的挑战.

主要方法:

  • 引入了以亲和为导向的共享策略 (AGSS),用于分阶段学习任务共享参数比例和分布.
  • 提出了一种细粒度梯度校正策略 (FGRS),以解决反向传播期间的元素智能梯度冲突.
  • 在标准的Swin变压器架构上构建了CTFS框架.

主要成果:

  • 在实例细分 (COCO数据集) 和语义细分 (ADE20K数据集) 上,CTFS取得了令人印象深刻的表现.
  • 通过使用共享参数比例作为预先知识,AGSS战略减少了网络优化的难度.
  • 在元素层面上,FGRS战略有效地缓解了梯度冲突.

结论:

  • 合并的变压器框架 (CTFS) 为同时实例和语义细分提供了有效的解决方案.
  • 拟议的AGSS和FGRS战略显著改善了网络优化和梯度冲突解决.
  • 在不复杂化底层Swin变压器架构的情况下,CTFS表现出强大的性能.