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相关概念视频

Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

154
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...
154
Types Of Transformers01:16

Types Of Transformers

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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...
976
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
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

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Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
653
Convolution Properties II01:17

Convolution Properties II

201
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
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相关实验视频

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GSB:对视觉变压器进行组叠加二元化,训练样本有限.

Tian Gao1, Cheng-Zhong Xu2, Le Zhang3

  • 1School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China.

Neural networks : the official journal of the International Neural Network Society
|January 24, 2024
PubMed
概括

视觉变压器 (ViT) 模型很大,并且容易因有限的数据而过度装配. 组叠加二元化 (GSB) 通过减少模型大小和计算提供了一个解决方案,甚至超出完全精确模型的性能.

关键词:
组叠加二元化组叠加二元化.培训数据不足 培训数据不足专注于自己的注意力视觉变压器 (ViT) 是一个视觉变压器.

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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
  • 深度学习 (Deep Learning) 是一种深度学习.

背景情况:

  • 视觉转换器 (ViT) 在计算机视觉方面表现出色,但受到很大的参数计数的影响,导致训练数据有限和计算需求高,导致过度装配.
  • 模型二进制化是一种压缩技术,通过使用1位参数和激活来减少模型大小和复杂性,为ViT的限制提供了潜在的解决方案.

研究的目的:

  • 调查视觉转换器 (ViT) 模型二元化的有效性.
  • 为解决应用现有的二元化技术对ViT的挑战,特别是注意力模块和价值向量中的信息丢失.
  • 提出一种新的二元化技术,即组叠加二元化 (GSB),以提高ViT的性能.

主要方法:

  • 开发了组叠加二元化 (GSB),这是一种针对视觉转换器量身定制的新技术.
  • 对二元化过程进行了研究并获得了改进的梯度计算方程,以减轻梯度不匹配.
  • 集成知识蒸以进一步提高二元化ViT模型的性能.

主要成果:

  • 现有的CNN二进制化方法不能很好地转移到ViTs,由于注意力和价值向量中的信息损失导致准确性下降.
  • 拟议的GSB技术有效地解决了这些问题,提高了二元化ViT的准确性.
  • 对有限数据数据集的实验表明GSB在二进制化方案中实现了最先进的性能,在某些指标上表现优于完全精确的ViT.

结论:

  • 模型二元化,特别是GSB,是压缩视觉变压器,减轻超拟合和减少计算负载的可行策略.
  • 与现有的二进制化方法相比,GSB在资源有限的场景中表现出优越的性能,甚至与完全精确的ViT相比.
  • 二元化过程本质上提供了规范化,有助于在数据不足的情况下进行训练.