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相关概念视频

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
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
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
Transformation01:26

Transformation

100
Microbial communities are dynamic environments where cell lysis releases free DNA into the surroundings. Other cells can take up this extracellular DNA through a process known as transformation.When a cell incorporates this foreign DNA into its genome, resulting in genetic modification, the process is known as transformation. Cells capable of this process are termed competent. Competence can be natural, as observed in certain bacteria and archaea, or artificially induced in the...
100
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

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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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基于变压器的图像颜色化

Min Xu1,2

  • 1School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai, 201209, China. minxu@sspu.edu.cn.

Scientific reports
|July 2, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种基于变压器的深度学习方法,用于自动灰度图像颜色化. 该方法实现了自然色彩和丰富的细节,显著改善了黑白图像增强.

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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
  • 图像处理 图像处理

背景情况:

  • 灰度图像缺乏视觉信息.
  • 手动调色是耗时的和主观的.
  • 需要自动化方法来实现现实的图像增强.

研究的目的:

  • 开发基于变压器的深度学习模型,用于自动灰度图像颜色化.
  • 为了提高彩色图像的准确性和视觉质量.
  • 为了利用深层架构和注意力机制来提取和预测特征.

主要方法:

  • 使用基于变压器的深层架构,堆叠编码器-解码器层.
  • 采用自我注意机制和上下文信息来预测色度组件 (例如,CIELAB中的ab通道).
  • 整合了输入光度通道 (L通道) 与预测的色度通道,用于最终的色化.

主要成果:

  • 在黑白图像彩色化方面取得了显著的性能改进.
  • 生成的图像呈现出自然的色彩和丰富的细节.
  • 与现有方法相比,证明了比现有方法更高的像素精度和视觉质量.

结论:

  • 拟议的基于变压器的方法有效地色化灰度图像.
  • 该模型的深度架构和注意力机制增强了特征提取和预测.
  • 结果显示,在图像增强和修复方面的实际应用具有很高的价值.