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相关概念视频

Transformers01:26

Transformers

1.7K
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...
1.7K
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

493
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...
493
Transformers in Distribution System01:27

Transformers in Distribution System

485
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...
485

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相关实验视频

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A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
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通过噪音视觉变压器改善食物图像识别

Tonmoy Ghosh, Edward Sazonov

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 3, 2025
    PubMed
    概括
    此摘要是机器生成的。

    噪音视觉变压器 (NoisyViT) 通过在训练期间引入噪音来增强食物图像识别,提高准确性. 这种计算机视觉技术在饮食评估和医疗保健应用中表现有前途.

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    科学领域:

    • 计算机视觉 计算机视觉
    • 机器学习 机器学习
    • 人工智能的人工智能

    背景情况:

    • 食品图像识别是复杂的,因为高变化.
    • 现有的模型与多样化的食物图像作斗争.

    研究的目的:

    • 调查噪音视觉变压器 (NoisyViT),以改善食品分类.
    • 评估NoisyViT在基准食品数据集上的表现.

    主要方法:

    • 在Food2K,Food101和CNFOOD-241数据集上微调NoisyViT.
    • 在学习过程中引入噪音,以减少任务复杂性和系统.

    主要成果:

    • 实现了95% (Food2K),99.5% (Food-101) 和96.6% (CNFOOD-241) 的顶级准确度.
    • 显著超过了最先进的食品识别模型.

    结论:

    • 噪音ViT为准确的食物图像识别提供了一个有希望的方法.
    • 潜在的应用包括饮食评估,营养监测和医疗保健.
    • 公共可用的代码有助于进一步研究基于视觉的食品计算.