Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Vision01:24

Vision

60.1K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
60.1K
Color Vision01:24

Color Vision

1.5K
Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
1.5K
Distillation: Vapor–Liquid Equilibria01:01

Distillation: Vapor–Liquid Equilibria

4.7K
Distillation is a separation technique that takes advantage of the boiling point properties of disparate elements in a mixture. To perform distillation, we begin by heating a miscible mixture of two liquids with a significant difference in boiling points (at least 20°C). As the solution heats up and reaches the bubble point of the more volatile component, some molecules of the more volatile component transition into the gas phase and travel upward into the condenser, which is a glass tube...
4.7K
Bacterial Transformation01:33

Bacterial Transformation

60.1K
In 1928, bacteriologist Frederick Griffith worked on a vaccine for pneumonia, which is caused by Streptococcus pneumoniae bacteria. Griffith studied two pneumonia strains in mice: one pathogenic and one non-pathogenic. Only the pathogenic strain killed host mice.
Griffith made an unexpected discovery when he killed the pathogenic strain and mixed its remains with the live, non-pathogenic strain. Not only did the mixture kill host mice, but it also contained living pathogenic bacteria that...
60.1K
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

2.0K
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.
2.0K
Transformers01:26

Transformers

1.9K
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...
1.9K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A novel drug series optimized to address cystic fibrosis and other CFTR deficiency diseases of human airways.

npj drug discovery·2026
Same author

Bridging Subjectivity in Affective Explanation Captioning via Consensus-Prompted Emotion Reasoning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

A multi-model carbon estimation framework for new urban district planning-integrating land use, transportation, and investment-based emission models.

Scientific reports·2026
Same author

Diaphragmatic Thickening Fraction and Excursion: Different Clinical Values in Non-Critically Ill Patients with AECOPD - An Exploratory Study.

International journal of chronic obstructive pulmonary disease·2026
Same author

Comparative effectiveness of different inhaler technique education modalities on clinical outcomes in patients with asthma and chronic obstructive pulmonary disease: a protocol for a systematic review and network meta-analysis of randomised controlled trials.

BMJ open·2026
Same author

Surgery versus radiotherapy after neoadjuvant immunochemotherapy in limited-stage small cell lung cancer.

Journal of thoracic disease·2026
Same journal

Exploiting audio-visual modalities in videos: Object detection via multi-stage bilateral coupling network.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Reliability-aware modality completion with cross-modal distillation for federated learning with missing modalities.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

IGFD-Net: Illumination-guided frequency decoupling for polarization image fusion.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Multiple-Strategies dung beetle optimizer and its applications in engineering optimization and bankruptcy prediction.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Aggregating global-scale pixel-wise forgery cues within a graph.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Finite-Time intermittent control for secure synchronization of Neutral-Type stochastic delayed neural networks under aperiodic DoS attacks.

Neural networks : the official journal of the International Neural Network Society·2026
查看所有相关文章

相关实验视频

Updated: Feb 9, 2026

Using Looming Visual Stimuli to Evaluate Mouse Vision
05:07

Using Looming Visual Stimuli to Evaluate Mouse Vision

Published on: June 13, 2019

12.3K

蒸结构知识从CNN到视觉转换器,以实现数据效率高的视觉识别.

Dingyao Chen1, Xiao Teng2, Xingyu Shen1

  • 1College of Computer Science and Technology, National University of Defense Technology, Changsha, 410073, Hunan, China.

Neural networks : the official journal of the International Neural Network Society
|February 7, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了基于特征的结构知识蒸 (FSKD),通过转移CNN特征来改进视觉转换器 (ViTs). FSKD 增强了 ViT 在视觉识别方面的性能,尤其是在有限的数据的情况下.

关键词:
注意力分布的注意力分布全球特征调整对齐.补丁之间的相似性知识的蒸知识的蒸.有限数据条件的条件.结构知识 结构知识

更多相关视频

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
09:29

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

13.5K
Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

3.5K

相关实验视频

Last Updated: Feb 9, 2026

Using Looming Visual Stimuli to Evaluate Mouse Vision
05:07

Using Looming Visual Stimuli to Evaluate Mouse Vision

Published on: June 13, 2019

12.3K
A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
09:29

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

13.5K
Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management
10:23

Author Spotlight: A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Published on: June 23, 2023

3.5K

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 知识蒸 (KD) 转移模型表示,通常对准输出逻辑.
  • 现有的CNN-to-ViT传输方法忽略了CNN特征中的丰富语义结构.
  • 这限制了视觉转换器 (ViTs) 在继承卷积神经网络 (CNN) 的诱导偏差.

研究的目的:

  • 提出基于特征的CNN-to-ViT结构知识蒸 (FSKD) 框架.
  • 将CNN功能中的语义结构知识与ViT的远程依赖能力集成.
  • 提高视觉识别中的ViT性能,特别是在低数据模式下.

主要方法:

  • 开发一个功能调整模块,以弥合CNN和ViT的代表性差距.
  • 整合一个全局特征对齐损失.
  • 引入贴片智能和注意力智能蒸损失,以实现贴片间的相似性和注意力分布转移.

主要成果:

  • FSKD有效地将语义结构知识从CNN转移到ViTs.
  • 该框架显著提高了ViT在视觉识别任务中的性能.
  • 在训练数据有限的场景中,绩效增长尤其显著.

结论:

  • FSKD提供了一种从CNN到ViTs的知识蒸的新方法.
  • 该方法成功地传输了丰富的结构信息,超出了简单的逻辑对齐.
  • FSKD 展示了 ViT 通用化和效率提升的潜力,特别是在数据稀缺的环境中.