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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

1.0K
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...
1.0K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

125
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
125
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

176
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...
176
Transformers in Distribution System01:27

Transformers in Distribution System

124
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...
124
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

94
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
94

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相关实验视频

Updated: Jul 20, 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

1.9K

一个生物灵感的定位嵌入网络,用于基于变压器的模型.

Xue-Song Tang1, Kuangrong Hao1, Hui Wei2

  • 12999 Renmin North Road, Songjiang Distinct, Shanghai, 201620, China.

Neural networks : the official journal of the International Neural Network Society
|July 29, 2023
PubMed
概括
此摘要是机器生成的。

这项研究介绍了一种由人类视觉启发的新型定位嵌入网络,以改进基于变压器的视觉模型. 这种生物可信的方法通过自适应地捕获空间信息来提高图像分类性能.

关键词:
背部通路建模的模型.图像的分类图像的分类.位置嵌入式嵌入式变压器 变压器 变压器零填充填充是零填充的

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科学领域:

  • 计算机视觉 计算机视觉
  • 神经科学是一个神经科学.
  • 人工智能的人工智能

背景情况:

  • 变压器网络具有先进的视觉模型,但位置嵌入需要进一步优化.
  • 位置嵌入对于在视觉模型中区分空间信息至关重要.

研究的目的:

  • 提出一种由人类视觉路径启发的新位置嵌入网络.
  • 通过生物可信的空间信息捕获,提高基于变压器的视觉模型的性能.

主要方法:

  • 一个双流架构,模拟空间感知的背部通路.
  • 对于局部特征使用大型零填充卷积,对于全球特征使用变压器.
  • 整合背部和腹部通路的相互作用,以全面理解空间.

主要成果:

  • 拟议的方法显著提高了各种数据集的图像分类性能.
  • 统计分析证实了该方法的有效性和生物可信性.
  • 简单的实施导致了显著的性能增长.

结论:

  • 生物启发的定位嵌入网络为推进视觉模型提供了一个有希望的方向.
  • 模拟人类视觉路径可以导致更有效和可解释的AI系统.
  • 这种方法增强了基于变压器的视觉架构中的空间特征提取.