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相关概念视频

Deconvolution01:20

Deconvolution

162
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
162
Transformers in Distribution System01:27

Transformers in Distribution System

103
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...
103
Energy Losses in Transformers01:21

Energy Losses in Transformers

880
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...
880
The Ideal Transformer01:26

The Ideal Transformer

399
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...
399
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

160
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...
160
Reducing Line Loss01:18

Reducing Line Loss

155
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
155

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Updated: Jul 9, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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CRefNet:使用解码器共享变压器学习一致的反射率估计

Jundan Luo, Nanxuan Zhao, Wenbin Li

    IEEE transactions on visualization and computer graphics
    |December 1, 2023
    PubMed
    概括
    此摘要是机器生成的。

    本研究介绍了CRefNet,这是一种深度学习模型,用于在内在图像分解中进行一致的反射率估计. CRefNet提高了全球和本地反射一致性,超过了最先进的方法.

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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.
    • 图像处理 图像处理

    背景情况:

    • 内在图像分解旨在将图像分成反射率和阴影组件.
    • 由于影响材料外观的照明变化,估计一致的反射率是具有挑战性的.
    • 现有的方法与全球和本地反射率的一致性作斗争.

    研究的目的:

    • 开发一个新的深度神经网络,CRefNet,用于准确和一致的反射率估计.
    • 在内在图像分解中改善全球和本地反射率的一致性.
    • 在内在图像分解方面推进最先进的技术.

    主要方法:

    • CRefNet采用混合变压器 - 卷积架构.
    • 一个新的变压器模块将图像特征转换为反射特征,捕捉远程交互.
    • 引入了一个辅助反射率重建任务和一个修正梯度过器.

    主要成果:

    • 通过其变压器模块,CRefNet实现了增强的全球反射一致性.
    • 辅助任务和梯度过器显著提高了反射率图的质量和局部一致性.
    • CRefNet的性能比最先进的方法高出10%的WHDR.

    结论:

    • CRefNet有效地解决了一致的反射率估计的挑战.
    • 拟议的方法增强了全球和本地反射一致性.
    • CRefNet在内在图像分解方面取得了重大进展.